Book

Principles And Practice Of Structural Equation Modeling

Authors:
... The importance of reporting the chi-squared test (C min = 357.29, C min d f = 2.41), as advised by Kline (2010Kline ( , 2016 for sample sizes between 75 and 200, was highlighted. The root mean square error of approximation (RMSEA = 0.09) and the comparative fit index (CFI = 0.90) were calculated in line with Kline's recommendations (Kline 2010(Kline , 2016, indicating a satisfactory fit between the observed data and the proposed model. ...
... C min d f = 2.41), as advised by Kline (2010Kline ( , 2016 for sample sizes between 75 and 200, was highlighted. The root mean square error of approximation (RMSEA = 0.09) and the comparative fit index (CFI = 0.90) were calculated in line with Kline's recommendations (Kline 2010(Kline , 2016, indicating a satisfactory fit between the observed data and the proposed model. ...
... 2024, 17, x FOR PEER REVIEW 12 of 23 highlighted. The root mean square error of approximation (RMSEA = 0.09) and the comparative fit index (CFI = 0.90) were calculated in line with Kline's recommendations(Kline 2010(Kline , 2016, indicating a satisfactory fit between the observed data and the proposed model. ...
Article
Full-text available
This paper investigates the relationship between sustainable entrepreneurship and financial inclusion, financial literacy, and entrepreneurial orientation. As sustainable entrepreneurship gains academic and practical interest, understanding factors that enable entrepreneurs to operate sustainably is fundamental. The manuscript uses an electronic questionnaire distributed to key economic stakeholders and performs partial least squares structural equation modeling on data from 169 respondents. The results show that entrepreneurial orientation has a positive and significant impact on sustainable entrepreneurship, with a beta coefficient of 0.878 and a probability value of less than 0.01. Financial literacy significantly influences sustainable entrepreneurship, with a beta coefficient of 0.389 and a probability value of less than 0.001, and it partially mediates its relationship with financial inclusion, showing a beta coefficient of 0.3 and a probability value of 0.013. Financial literacy and financial inclusion are positively correlated, with a beta coefficient of 0.771 and a probability value of less than 0.05. However, the impact of financial inclusion on sustainable entrepreneurship is negative and insignificant, with a beta coefficient of −0.392, and there is no evidence that entrepreneurial orientation moderates the link between financial literacy and sustainable entrepreneurship. The findings provide valuable insights for Moroccan policymakers to promote entrepreneurship, suggesting that financial literacy plays a crucial role in enhancing sustainable business practices. The study emphasizes the need for Morocco to adapt to current programs and create a supportive financial environment for entrepreneurs. Due to a lack of comprehensive datasets, the study’s conclusions are limited and might not accurately reflect the entire landscape.
... A figura 2 refere-se ao resumo do processo metodológico seguido no estudo. (Hair Jr. et al., 2010;Brown, 2015;Kline, 2023;Freitas et al., 2022). ...
... Nota-se que as dimensões Estratégia de Inovação e Análise de Custos evidenciaram, em uma escala de 1 a 5, valores inferiores a 3. Em um entendimento geral, a obtenção de valores maiores que 3 poderiam denotar uma boa adequação às perguntas realizadas no questionário, para um melhor desempenho na dimensão. A dimensão Visão de Mercado apresentou as melhores médias em suas questões, o que demonstra uma busca pelos parâmetros de mercado de maneira mais adequada na amostra analisada, seguindo o regramento da dimensão imposto pelos seus quesitos (Hair Jr. et al., 2010;Brown, 2015;Kline, 2023). (Hair Jr. et al., 2010;Brown, 2015;Kline, 2023 amostra (Hair Jr. et al., 2010;Brown, 2015;Kline, 2023). ...
... A dimensão Visão de Mercado apresentou as melhores médias em suas questões, o que demonstra uma busca pelos parâmetros de mercado de maneira mais adequada na amostra analisada, seguindo o regramento da dimensão imposto pelos seus quesitos (Hair Jr. et al., 2010;Brown, 2015;Kline, 2023). (Hair Jr. et al., 2010;Brown, 2015;Kline, 2023 amostra (Hair Jr. et al., 2010;Brown, 2015;Kline, 2023). ...
Article
Full-text available
Instituições Públicas de Pesquisa (IPP) desempenham um papel crucial no desenvolvimento nacional, contudo enfrentam desafios diante de mudanças políticas, econômicas e sociais. Este estudo propõe um modelo de forecasting tecnológico para IPP, integrando inovação, custos e potencial de mercado com a Modelagem por Equações Estruturais. Conforme as leis de inovação, as IPP são encarregadas de contribuir economicamente e socialmente através do desenvolvimento tecnológico. Em uma pesquisa com 104 servidores de três IPP no Piauí, o modelo proposto evidencia que mecanismos de forecasting tecnológico podem influenciar a análise de custos, estratégias de inovação e a visão de mercado. Com base nos questionários aplicados, evidenciou-se a necessidade de capacitação em Propriedade Intelectual e de investimentos nos Núcleos de Inovação Tecnológica. Tais ações visam aprimorar os processos de Transferência de Tecnologia (TT). Observa-se que análise de custos, estratégias de inovação e visão de mercado favorecem uma avaliação e valoração adequada das tecnologias.
... 1), we estimate a fully recursive model to identify those effects net of all other inf luences controlled in the model. Following recommendations and for parsimony, in the final model we trim nonsignificant paths while keeping residual correlations even if they were not significant (Kline 2016). ...
... Model fit is commonly considered acceptable when CFI > .90, TLI > .90, and RMSEA < .08 (Kline 2016;McDonald and Ho 2002). Table 1 reports descriptive statistics for all variables. ...
Article
Full-text available
In his path-breaking monograph, Class and Conformity, Melvin Kohn reasoned that parents prepare their children for the same conditions of work that they themselves experience. Kohn and his colleagues’ research focused on the influence of parental self-direction at work on parental child-rearing values and practices, as well as the self-directed values of children. The intergenerational transmission of occupational self-direction from parents to the succeeding generation of adult children, strongly implied by Kohn’s analysis, has not been empirically tested. Using two-generation longitudinal data from the Youth Development Study (N = 1139), we estimate a structural equation model to assess the intergenerational continuity of occupational self-direction. We find evidence supporting a key inference of Kohn’s analysis: that self-direction at work, a primary feature of jobs of higher social class standing, is transmitted across generations via self-directed psychological orientations, operationalized here as intrinsic work values. Intrinsic values also significantly predicted second-generation educational attainment, contributing further to the reproduction of socioeconomic inequality. The findings enhance understanding of the intergenerational transmission of advantage.
... Regression analysis is a statistical method used to quantify the extent to which the independent variable or factors account for the variability observed in the dependent variable. While multiple regression analysis is constrained to using only observable variables, the fundamental ideas of this method can still be applied in structural equation modeling [20]. The statistical analysis technique allows for the examination of research hypotheses by creating models that represent intricate connections between numerous observables ( Figure 1). ...
... When the distribution is long and thin and very flat (mesokurtic), indicating a large number of outliers, negative kurtosis is present. When the kurtosis index has an absolute value more than 10.0, it may indicate an issue; values exceeding 20.0 are considered extreme (20). Given that distributions deviate from normality in at least four ways, univariate normality is particularly crucial to take into account. ...
... These high values suggest that the hypothesized relationships align well with the observed data, supported by an adequate sample size, high data quality, and appropriate estimation methods. However, the results from CFA indicated a Chi-square over Degrees of Freedom value of 5.72 (χ 2 / df = 5.72), which exceeds the commonly recommended threshold of 5 for an acceptable model fit (Rex, 1998). This may primarily be due to the large sample size, which is known to inflate chi-square values and make it overly sensitive to minor discrepancies (Rex, 1998). ...
... However, the results from CFA indicated a Chi-square over Degrees of Freedom value of 5.72 (χ 2 / df = 5.72), which exceeds the commonly recommended threshold of 5 for an acceptable model fit (Rex, 1998). This may primarily be due to the large sample size, which is known to inflate chi-square values and make it overly sensitive to minor discrepancies (Rex, 1998). Based on these indices and their acceptable ranges, the model can be considered a good fit (Hu and Bentler, 1999). ...
Article
Full-text available
Massive changes in many aspects related to social groups of different socioeconomic backgrounds were caused by the COVID-19 pandemic and as a result, the overall state of mental health was severely affected globally. This study examined how the pandemic affected Sri Lankan citizens representing a range of socioeconomic backgrounds in terms of their mental health. The data used in this research was gathered from 3,020 households using a nationwide face-to-face survey, from which a processed dataset of 921 responses was considered for the final analysis. Four distinct factors were identified by factor analysis (FA) that was conducted and subsequently, the population was clustered using unsupervised clustering to determine which population subgroups were affected similarly. Two such subgroups were identified where the respective relationships to the retrieved principal factors and their demographics were thoroughly examined and interpreted. This resulted in the identification of contrasting perspectives between the two groups toward the maintenance and the state of social relationships during the pandemic, which revealed that one group was more “socially connected” in nature resulting in their mental state being comparatively better in coping with the pandemic. The other group was seen to be more “socially reserved” showing an opposite reaction toward social connections while their mental well-being declined showing symptoms such as loneliness, and emptiness in response to the pandemic. The study examined the role of social media, and it was observed that social media was perceived as a substitute for the lack of social connections or primarily used as a coping mechanism in response to the challenges of the pandemic and results show that maintaining social connections physically or via online rather than the use of social media has helped one group over the other in decreasing their symptoms such as emptiness, loneliness and fear of death.
... Buna göre, bir modele ait kabul edilebilir değerler incelenirken sadece bir uyum değerine değil de birkaç farklı değere birlikte bakmak gerektiği ifade edilmektedir. Kline (2015) yapısal eşitlik modelleri için en azından ki-kare modeli, RMSEA, CFI ve SRMR indekslerinin raporlanması gerektiğini ifade etmektedir (Kline, 2015). İstatistiksel çalışmalarda en çok kullanılan uyum iyiliği indeksleri aşağıda verilmiştir. ...
... Buna göre, bir modele ait kabul edilebilir değerler incelenirken sadece bir uyum değerine değil de birkaç farklı değere birlikte bakmak gerektiği ifade edilmektedir. Kline (2015) yapısal eşitlik modelleri için en azından ki-kare modeli, RMSEA, CFI ve SRMR indekslerinin raporlanması gerektiğini ifade etmektedir (Kline, 2015). İstatistiksel çalışmalarda en çok kullanılan uyum iyiliği indeksleri aşağıda verilmiştir. ...
Book
Full-text available
Ödeme gücünün göstergelerinden biri olan gelirin vergilendirilmesinde, mükelleflerin gerçek vergi yüklerinin belirlenmesi, toplumun vergi adaleti algısı açısından önem arz etmektedir. Dolayısıyla hem vergilendirilecek olan kişilerin ve vergiye tabi ücretlerin belirlenmesi, hem de doğru vergilendirme yönteminin tespit edilmesi gibi teknik konularda normatif yaklaşımların benimsenmesi gerekmektedir. Doğru tekniklerin uygulanmadığı veya uygulanmasına yönelik düzenlemelerin yapılmadığı bir sistemin toplum tarafından gayri adil olarak algılanması kaçınılmazdır. Bu bakımdan bu çalışmada, literatürde ödeme gücüne ulaşma teknikleri olarak ifade edilen kavramların, mükelleflerin vergi adaleti algılarına yönelik etkisi akademisyenler özelinde araştırılmak istenmiştir.
... However, it is important to note that constraining parameters can be helpful when dealing with parameters that exhibit excessive variance, ensuring a more stable and reliable estimation process. This approach aligns with the principles discussed in Byrne (2016) and Kline (2016), which emphasize the importance of appropriately applying constraints to improve model quality while maintaining theoretical coherence. The likelihood ratio test (LRT) showed that Social Games (Model 1) was more strongly associated with EQ-i subscales than the Titles Games test (Model 2), (∆x 2 = 4.39, ∆df = 1, p = 0.36) (See Figure 1). ...
... However, it is important to note that constraining parameters can be helpful when dealing with parameters that exhibit excessive variance, ensuring a more stable and reliable estimation process. This approach aligns with the principles discussed in Byrne (2016) and Kline (2016), which emphasize the importance of appropriately applying constraints to improve model quality while maintaining theoretical coherence. The likelihood ratio test (LRT) showed that Social Games (Model 1) was more strongly associated with EQ-i subscales than the Titles Game test (Model 2), ( = 4.39, Δdf = 1, p = 0.36) (See Figure 1). ...
Article
Full-text available
The current study examined the relationship between creative potential, estimated with tests of divergent thinking (DT), and emotional intelligence (EI). Previous research has hinted at a relationship, but the EI–DT relationship may differ as a function of the tasks and the specific components of EI. With this in mind, the present investigation compared two DT tests (Social Games vs. Titles Game) and examined whether or not the Interpersonal and Intrapersonal subscales of EI were more associated with DT than the Adaptability and Stress Management EI subscales. The youth version of the Bar-On Emotional Quotient Inventory (EQ-i: YV) was used to measure EI. The measure of EI and the two DT tests were administered to 244 male and female gifted (N = 125) and nongifted (N = 119) high school students in Saudi Arabia. The first objective was to examine whether the EI–DT relationship differs based on the nature of the task of the two DT tests used in the current study (Social Games vs. Titles Game). The second objective was to test whether the Interpersonal and Intrapersonal subscales of EI are more associated with DT than the Adaptability and Stress Management EI subscales. Canonical correlation analysis showed that the relationship between the Social Games test and EI was stronger than the relationship between the Titles Game test and EI. Two path analyses were run: one for the total sample and the second for the gifted sample. The likelihood ratio test showed that the Social Games test was more associated with EQ-i subscales than the Titles Game test for both samples. As expected, the Inter- and the Intrapersonal subscales of the EQ-i were more highly related to Social Games fluency and originality scores compared with the Stress Management and Adaptability subscales. Limitations and future directions are discussed.
... The general approach often used to analyze TRA/TPB and IBM is structural equation modeling (SEM). SEM is used to see the relationship between TRA/TPB and IBM through a technical language that can classify theoretical components with precision [13,14] and provide statistical models such as multiple variances in path analysis to perform empirical analysis [15]. Although not all TRA/TPB/IBM theory analyses use SEM, SEM is often used to answer more complex questions and measure latent variables. ...
... This study aims to test the model and the hypothesis of the factors that influence abortion based on the Integrated Behavioral Model theory. SEM analysis was used in relation to the TRA / TPB and IBM [13,14]. The data analysis used STATA [16]. ...
Article
Full-text available
Stigma on abortion has limited the study of abortion in several countries, including Indonesia. Understanding factors of abortion can improve programs and policies aimed at increasing women’s sexual and reproductive health and rights, especially abortion. This study aims to draw a picture of the behavioral determinants of women who had abortions. This cross-sectional study utilized data from a community-based survey of 8,969 randomly selected women aged 15-49 in six provinces in Java. Data were collected via an interviewer-administered structured questionnaire, collecting information on socio-demographic characteristics, experience using contraception, pregnancy, abortion, partner violence, and other issues related to reproductive health. Structural Equation Modeling Analysis was used to get an overview of the structural determinants of women who had abortions based on the concept of Integrated Behavioral Model Theory. Model fit with RMSEA value = 0.037, CFI = 0.924, and SRMR =0.048. Intention shows the most significant direct effect on abortion. The experience of physical and sexual violence, the attitude toward the impact of ending pregnancy, and the lack of contraception knowledge have a direct effect on increasing the intention to have an abortion.
... In research, the reliability and validity of the sample are major concerns since they ensure the accuracy and consistency of the findings. After removing outliers, this research has 255 valid respondents, which is more than the minimum recommended for SEM, as suggested by Kline (2011). The sample was carefully selected to include a diversified range of participants, such as students, educators, and working professionals from various private higher education institutions in Myanmar. ...
... Yet, following a pilot study, 16 indicators were deemed unreliable or invalid, leaving us with the necessity to eliminate them. According to Kline (2011), each construct should be assessed by a minimum of three indicators. Male respondents make up 43.1% of the sample, while female respondents make up 56.9% of the total in the remaining valid dataset. ...
... Additionally, a Shapiro-Wilk test was conducted, with the results summarized in Table 3, to provide a comprehensive examination of data normality, ensuring the accuracy and robustness of subsequent statistical analyses. According to the literature, skewness and kurtosis values between +2.0 and −2.0 are generally accepted as indicators of normal distribution (George and Mallery 2010;Kline 2023). For this study, skewness and kurtosis values for the WMS and WM-PTF tests, as well as the visual and verbal memory sub-tests in both experimental and control groups, were all within this range, suggesting normal distribution. ...
Article
Full-text available
This study examines the effects of a working memory (WM) intervention package on the WM performance of students with Specific Learning Disabilities (SLDs). A pre-test post-test experimental design was applied with 40 students, divided equally into experimental (20 students) and control groups (20 students). Data were collected using the Working Memory Scale (WMS), Raven’s Standard Progressive Matrices (RSPM), and the Working Memory Performance Tasks Form (WM-PTF). The experimental group demonstrated statistically significant improvements in WMS and WM-PTF scores relative to the control group (p < 0.006, d = 1.96 for WMS; d = 1.42 for WM-PTF). Additionally, a positive correlation was observed between the increase in WM performance and intelligence scores, suggesting that intelligence may influence WM gains. In conclusion, the WM intervention package was significant in improving the WM performance of students with SLDs, indicating that such interventions have significant potential for enhancing cognitive functions and memory. These findings highlight the critical role of WM interventions in contributing to the cognitive development of students with learning difficulties.
... De las personas que atendieron la consulta y del agrupamiento por sexo se obtuvo que (Kline, 2011;Ramlall, 2017). ...
Article
Full-text available
La pandemia de COVID-19 ha transformado profundamente las estrategias educativas empleadas en diversos cursos universitarios. En particular, los cursos de Agronegocios no han sido ajenos a estos cambios. El objetivo del estudio fue explorar la percepción del estudiantado de Agronomía respecto a cómo las adaptaciones pedagógicas requeridas durante la pandemia, incluida la transición entre modalidades presenciales y virtuales, afectaron su motivación y capacidad de adaptación a las nuevas tecnologías. Se llevó a cabo un estudio con 84 estudiantes de grado de la carrera de Agronomía de la Universidad de Costa Rica, Sede Rodrigo Facio, durante el mes de junio de 2022. Las personas participantes completaron un cuestionario estructurado con 30 ítems, en el que se evaluaron aspectos como el perfil demográfico, la conectividad a Internet, la disponibilidad de equipamiento informático, la aceptación de tecnologías virtuales, la percepción sobre la calidad de los contenidos impartidos, y la motivación personal del estudiantado. Los datos recopilados fueron analizados utilizando modelos de ecuaciones estructurales para examinar las relaciones causales entre las variables de interés. Se observó que la motivación personal tuvo un efecto significativo (β=0.23) en la percepción del estudiantado sobre la enseñanza de Agronegocios durante la pandemia. Este estudio subraya la importancia que el estudiantado de Agronomía le otorga a la calidad de la enseñanza por parte del profesorado y a la realización de actividades prácticas como impulsoras clave de su motivación en el aprendizaje de los contenidos de Agronegocios.
... Standartlaştırılmış regresyon katsayılarında genellikle işarete bakılmaksızın 0.60 ve üzeri yük değeri yüksek, 0.30-0.59 arası yük değeri orta düzeyde tanımlanıp değişken çıkarmada göz önünde bulundurulabilir (Kline, 2011). Model uyum istatistikleri için 2 / df χ oranının 0.10 ile 3 arasında olması, söz konusu indekslerin 0.80 ile 0.90 arasında olması kabul edilebilirken 0.90'ın üzerinde olması iyi uyumu, RMSEA'nın 0.00-0.10 ...
Chapter
Full-text available
Türkiye’de gerçekleştirilen bu çalışmada, Türkiye’nin kolektivist bir ülke olduğu gerçeği de göz önünde bulundurularak ve bu toplumlarda ki ilişkilerin ahlâki bir temeli olduğu gerçeğinden hareketle, ahlâki kimlik ve kolektif kimlik faktörlerinin etik tüketim davranışı üzerinde ki etkisi araştırılmaktadır.
... The marketing innovation factor had standardized regression weights ranging from .784 to .616 and R2 values ranging from .614 to .380. Additionally, the examination of the goodness of fit between the evaluation framework and empirical data through accepted standard criteria is presented in Table 2. (1989), Kline (1998) Therefore, no observed variables were removed. Subsequently, after assessing the modification index and making adjustments as recommended by the software, a new analysis was conducted to obtain standardized coefficient values, conduct hypothesis testing, and determine the influence of factors affecting organizational survival. ...
Article
Retail food businesses are important contributors to the economic stability of nations, contributing to the economy in different ways, including providing jobs in the supply chain pipeline. Global events like the pandemic arising from the spread of COVID-19 threatened the aptitude of retail food outlets to operate due to the restrictions put in place to mitigate the spread of the virus. The objective of this research is to investigate the determinants that impact the longevity of organizations in the food retail industry and construct a survival model that accounts for these characteristics considering the COVID-19 pandemic, and examining the roles of variables such as organizational survival, external general environment, corporate governance policy, transformational change management, economic condition, and marketing innovation. The study utilized quantitative methodology, employing a survey questionnaire to gather data from a sample of 360 entrepreneurs. Subsequently, the data was analyzed using statistical analysis and the Structural Equation Model (SEM). The research findings reveal that the external general environment, transformational change management, economic conditions, corporate governance policies, and marketing innovation have statistically significant positive impacts on organizational survival. Consequently, food retail businesses must adapt within the COVID-19 context, under evolving external conditions, to strategize for enhanced competitive capabilities. This includes managing change and economic conditions for survival in a COVID-19 pandemic characterized by rapid economic shifts, human behavioral changes, and adaptive governance policies that align with situations. These findings can be applied to organizational structures, addressing weaknesses and further enhancing organizational strengths to create innovative marketing approaches that align appropriately with current circumstances for organizational survival. An important limitation of the study is that data were collected from only 360 food retailers in Thailand, representing a partial population of the food retail business in Thailand, hence limiting the generalizability of the results beyond the context of the study and other countries.
... O ajustamento do modelo fatorial aos dados foi avaliado por meio dos índices de modelos de equações estruturais, considerando os seguintes critérios: a estatística do χ 2 , que compara a matrix de variância-covariância implícita no modelo com a matrix de variância-covariância observada nos dados; o índice comparativo do ajustamento (CFI), que compara o modelo especificado com um modelo nulo sem trajetórias ou variáveis latentes; a raíz do erro quadrático médio de aproximação (RMSEA), que compara a matrix de variância-covariância implícita no modelo com a matrix de variância-covariância observada nos dados, ajustada para o tamanho da amostra e para a complexidade do modelo. Tomou-se por referência os parâmetros de um bom ajustamento que são representados por: valor de χ 2 /gl inferior a 3(Schermelleh-Engel et al., 2003); CFI de 0.90 ou superior(Bentler, 1990); e RMSEA de 0.08 ou inferior(Kline, 2011; Schermelleh- Engel et al., 2003). Adicionalmente, foi usado o critério relativo ao resíduo quadrático médio (SRMR), semelhante ao RMSEA, o qual considera como aceitáveis valores de 0.08 ou abaixo(Schermelleh-Engel et al., 2003). ...
Article
Full-text available
Instrumentos que avaliam as interações entre práticas parentais e comportamentos de forma conjunta são raros; o RE-HSE-P possui essas características. Este estudo teve como objetivo ampliar as propriedades psicométricas do RE-HSE-P com dois objetivos principais: (1) Verificar a validade interna e a consistência interna do RE-HSE-P por meio de análise fatorial confirmatória, considerando a estrutura interna do modelo original, definido pela análise fatorial exploratória com dois fatores -positivo e negativo- relativos às interações entre práticas parentais e comportamentos; e (2) Avaliar a validade discriminativa do instrumento em duas faixas etárias, crianças (pré-escolares e escolares) e adolescentes, utilizando a distribuição dos percentis para identificar padrões de interação nas práticas parentais e comportamentos.. Foram participantes 360 pais/cuidadores de meninos e meninas, com idade variando entre 4 e 16 anos, os quais responderam a instrumentos aferidos sobre práticas educativas e comportamentos infantis. Procedeu-se a análise fatorial confirmatória, tomando por referência os índices de modelos de equações estruturais e os parâmetros de um bom ajustamento; para a consistência interna calculou-se o alpha de Cronbach e utilizou-se percentis por grupos para estimar pontos de corte para interações de risco/não risco. Os resultados indicaram bons indicadores psicométricos, confirmando a estrutura de dois fatores (Total Positivo e Total Negativo). O RE-HSE-P pode ser utilizado para rastreio de interações familiares de risco/não risco de pais /cuidadores com crianças e adolescentes, podendo auxiliar na promoção de intervenções preventivas e remediativas.
... Furthermore, the Variance Inflation Factor (VIF) values remain well below the threshold of 3.3 (Kock 2015), which addresses concerns about multicollinearity within the model and suggests that the predictor variables are not excessively correlated. It is crucial to maintain the integrity of structural relationships under investigation and ensure that the results are not distorted by redundant information (Kline 2023). Collectively, these findings affirm that the model exhibits strong reliability and validity, providing a robust foundation for further analysis and interpretation. ...
Article
Full-text available
This study explores the interplay between tax incentives, creative compliance, and innovation in enhancing business resilience and sustainability among micro, small, and medium enterprises (MSMEs) in Indonesia, addressing gaps in the existing literature regarding their interrelationships during crises. A cross-sectional survey of 360 MSMEs was conducted, utilizing the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach to analyze complex relationships among variables. The findings reveal that creative compliance, including tax planning and avoidance, does not directly impact resilience or sustainability. While tax incentives did not significantly enhance resilience during crises, they contributed to long-term sustainability. Innovation emerged as a critical factor linking creative compliance to business success and fully mediating the effects of tax incentives on resilience. This study emphasizes the necessity for MSMEs to prioritize innovation in their strategies, particularly in conjunction with effective tax practices, and highlights the need for government support through simplified regulatory frameworks to foster an innovative business environment. Limitations include the challenges of incorporating control variables in SEM and the need for further research into the long-term effects of these factors on sustainable performance.
... However, as indicated by several scholars (e.g., MacCallum et al. 1999;Wolf et al. 2013), one size does not fit all, and more is not always better. Following Kline (2023), our study, to a large extent, showed a normal distribution and therefore the sample size was adequate; however, we suggest future research to employ larger sample sizes. Regarding the moderating effects, we acknowledge that one way to gain further insights on the moderating role of individual differences would be through the application of more advanced statistical modeling approaches such as Johnson-Neyman-Intervall (JNI). ...
Article
Full-text available
Limited research has focused on consumption reduction as one potential pathway to meet sustainable development goals. This paper investigates consumers’ intentions to undertake consumption reduction through the lens of an extended theory of planned behavior (TPB), where selected individual differences, namely the need for evaluation (NE) and self-referencing (SR), are given considerable attention. In total, 226 respondents participated in this web-based survey study. The results from structural equation modeling analysis confirm that the extended theory of planned behavior effectively explains consumers’ intentions to undertake consumption reduction. Notably, the individual differences of the NE and SR each uniquely moderate the relationships within the TPB model. This study provides a theoretical contribution by integrating the selected moderators (i.e., the NE and SR) into the TPB framework, increases the TPB’s predictive power, and further provides a novel understanding of the underlying influences of individual differences on consumers’ intentions to undertake consumption reduction for the benefit of the environment. Moreover, the findings offer practical implications for policymakers and social marketers in designing tailor-made interventions and consumption reduction strategies by considering the important role of individual differences.
... As shown in Table 4, all the square roots of the AVE values exceeded the correlations of the constructs. All the HTMT scores were below the expected standard of 0.80 (Kline 2023), revealing no discriminant validity issues. Table 4 displays the outcomes. ...
Article
Full-text available
This article aims to investigate the factors that affect behavioural intention (BI) and user behaviour (UB) among Arabian users of generative artificial intelligence (GenAI) applications in the context of media content creation. The study’s theoretical framework is grounded in the unified theory of acceptance and use of technology (UTAUT2). A sample of 496 users was analysed using the partial least squares structural equation modelling technique (PLS-SEM). The results revealed that BI is significantly influenced by performance expectancy, effort expectancy, social influence, hedonic motivation, habit, and user trust, with hedonic motivation having the greatest impact. In terms of UB, facilitation conditions, habit, user trust, and BI were all found to have a positive and significant impact. This study contributes to the existing theory on the utilisation of GenAI applications by organising findings pertaining to the use of AI technology for media content creation.
... Two necessary conditions for model identification are that the degrees of freedom are greater than or equal to zero d f ≥ 0 and that the number of estimated parameters does not exceed the number of observations (Kline 2016). According to Vázquez (2013), to calculate the number of non-redundant entries in the covariance matrix, the following equation can be used: ...
Article
Full-text available
In Mexico, approximately 55% of the working population is employed informally, contributing 24.4% to the Gross Domestic Product (GDP) in 2022. This study analyzed the impact of wages, taxes, government spending, and unemployment on the informal economy of Mexico from 1980 to 2022, as well as its relationship with the tertiary sector’s contribution to the GDP. The methodology of the study was structural equation modeling. The findings of this study revealed that an increase in taxes, the unemployment rate, and the minimum wage in Mexico tends to be accompanied by a rise in informal employment. Finally, a unitary change in the latent variable informality affected the growth of the tertiary sector’s contribution to the GDP by 0.37 units.
... indicating an acceptable fit in accordance with the established criteria, thereby satisfying the requirements for model fit adequacy. This implies that there were no discernible differences in the measurements derived from empirical modeling or those substantiated by the data based on criterias from Kline [13] presented in Table IV. Although the fit parameter of Chi-Square/df = 3.91 did not meet the criteria of 2-3, this point could be disregarded as the respondents included a large sample size (N=500). ...
Conference Paper
Full-text available
Higher education fostered university students' academic competence and professional development, especially post-pandemic. Academic resilience, crucial for student success, lacked a validated Indonesian tool. Validating the ARS-30 Scale was essential to evaluate students' risk assessment and adaptation to academic challenges. The study, involving 500 university students from various cities, aimed to validate the academic resilience scale in the Indonesian context. Data collection included translation, validity, and reliability assessments. The Content Validity Index (CVI) values ranged from .87 to 1. Confirmatory factor analysis (CFA) showed an acceptable fit with Chi-Square=289.629, RMSEA=.053, CFI=.945. And factor loadings from .50 to .73. The Cronbach alpha was .735. Fourteen items showed a good fit, and sixteen items showed a poor fit. The study concluded that the scale effectively measures academic resilience in Indonesian university students.
... We checked the following fit indices: the Chi-square statistic (χ 2 ), the comparative fit index (CFI), the root-mean-square error of approximation (RMSEA), and the standardised root-mean-square residual (SRMR). An acceptable level of model-data fit requires that the CFI be larger than 0.90 and the RMSEA and the SRMR be smaller than 0.08 (Kline 2015). ...
Article
The ability to produce a well-written text in English using multiple material resources, such as integrated writing (IW), is widely recognised as a crucial literacy skill for tertiary students. While previous researchers have extensively examined the factors contributing to second language (L2) English integrated writing, the impact of students' first-language (L1) Chinese writing strategic knowledge and skills on L2 writing performance has received limited empirical attention. Therefore, this study aimed to investigate the simultaneous relationship between L1 and L2 writing strategy use, L1 writing skills, and L2 IW performance among 239 Chinese university students. Results from structural equation modelling revealed that L1 IW strategy use could predict L2 IW strategy use. Furthermore, the use of L1 IW strategies indirectly predicted L2 IW performance through the use of L2 IW strategies. This study contributes to the existing literature by extending research on cross-language effects in the IW context. Additionally, based on the findings, pedagogical implications for teaching IW across two languages are proposed.
... This makes it an appropriate technique for assessing the direct and mediating effects of latent predictor variables on outcome variables. In addition, the main statistical analysis followed the proposal of (Kline 2016(Kline , 2023 for statistical analysis and testing structural equation models and the weighted least squares mean adjusted (WLSM) was used. Model goodnessof-fit indices were evaluated according to the proposals of Kline and Escobedo (Escobedo et al. 2016;Kline 2016). ...
Article
Full-text available
(1) Background: In university contexts, the effectiveness of work teams is vital for institutional success and the personal development of an institution’s members. Objective: Our aim is to understand the relationships between emotional intelligence, team leadership, organizational culture, work climate, and creative synergy with team effectiveness. (2) Methods: We used a cross-sectional predictive design study using structural equation modeling (SEM), in which 512 surveys of employees of a private Peruvian university were analyzed. (3) Results: Leadership and emotional intelligence were found to significantly improve team effectiveness. In addition, organizational culture, work climate, and creative synergy act as mediators in these relationships, enhancing team effectiveness. The adjusted model presented adequate incremental (x2=9452.498, gl=3391, p<0.001) and comparative (TLI=0.998, CFI=0.998, RMSEA=0.017 y SRMR=0.033) goodness-of-fit indices. (4) Conclusions: The results showed that the development of emotional competencies and leadership skills is essential to optimize the effectiveness of work teams in universities. This integrated model not only provides a solid theoretical framework for future research, but also offers practical recommendations for improving the management and performance of work teams.
Article
Full-text available
This study aims to determine the factors influencing school violence among students in emblematic educational institutions in the Junín region post-pandemic. A quantitative and explanatory study was conducted with a sample of 1,656 students, aged 12 to 18, selected through simple random sampling. Data collection instruments included a questionnaire for assessing various factors and the School Bullying and Violence Test (AVE) for measuring school violence. Validity was ensured through expert judgment and a pilot test, while reliability was assessed using Cronbach’s alpha, with values of 0.832 and 0.802. Structural equation modeling was used for analysis. The personal factor (β = 0.39, p < 0.001) had a direct and significant influence on school violence. The family factor showed a low and negative relationship (β = −0.06, p < 0.017). The educational factor also presented a negative relationship (β = −0.16, p < 0.001), indicating that changes in norms and structure could reduce violence. Adolescents’ personal factors, such as emotional distress, irritability, and anxiety, directly influence school violence. The family factor did not significantly influence violence, as families felt more cohesive during confinement, acting protectively post-pandemic. The educational factor impacts school violence when norms are not enforced, supervision is insufficient, and spaces are limited.
Article
Full-text available
Objectives This study aimed to determine the relationship between mindfulness, self-esteem, and decision-making. The study focused to examine the relationship primarily between mindfulness and decision-making, with self-esteem as a mediator and experience as a moderator among teachers in Saudi Arabia. Methods A survey was conducted among teachers in Saudi Arabia and was completed by 525 teachers (67.8% were females and 32.2% were males, with an average age of 38.25 years, standard deviation [SD] = 8.72). Participants were Arabic-speaking teachers who were selected from public and private schools in Saudi Arabia. They were selected via direct contact with schools in Riyadh. Using the snowball spreading techniques, the teachers were recruited from elementary, middle, and high schools. Adolescent and Adult Mindfulness Scale (AAMS), Rosenberg Self-Esteem Scale (RSES), and Decision-Making Scale were used to obtain information on the variables. Results Mindfulness was significantly and positively correlated with decision-making and positive self-esteem and negatively correlated with negative self-esteem. Decision-making was significantly positively correlated with positive self-esteem and negatively correlated with negative self-esteem. Moreover, positive self-esteem partially mediated the relationship between mindfulness and decision-making, indirectly. However, mindfulness was not predicted by decision-making through negative self-esteem. A multigroup analysis showed that the mediational model was moderated by high teaching experience. Conclusion The results prove that mindfulness and self-esteem are associated with decision-making. Self-esteem and mindfulness for teachers increase their awareness of the problems they face daily in the classroom. Additionally, more experienced teachers are more confident and portray better decision-making skills.
Article
Full-text available
Background Patient Reported Outcomes Measurement Information System Fatigue Short-Form (PROMIS-F-SF) is a self-administered, patient reported outcome (PRO) designed to assess fatigue in healthy and clinical populations and for tracking progress during treatment for disorders complicated with fatigue. Methods Patients in the Mental Health Service Outpatient Clinics and healthy volunteers were invited to complete a survey, which included the Danish translation of the PROMIS-F-SF, the Chalder Fatigue Scale (CFS-11), and measures of depression and anxiety. We conducted a confirmatory factor analysis of the previously suggested single-factor structure of the instrument. We furthermore evaluated the construct validity of the PROMIS-F-SF by means of its relationship with the CFS-11. Finally, we evaluated the utility of the PROMIS-F-SF to identify patient-status by conducting receiver operating characteristic curves. Results 70 healthy volunteers and 62 patients completed the instruments. The PROMIS-F-SF had a average fit to the previously reported single-factor structure. Cronbach’s alpha and McDonald’s omega showed good internal reliability (α = 0.96, ωtotal = 0.97). PROMIS-F-SF score was positively correlated with the CFS-11 ( r =.76) and it correlated highly with depression ( r =.78) and anxiety ( r =.74) score. The optimal cut-off point in the ROC-analyses was 15, which yielded a sensitivity of 89% and a specificity of 67% in the prediction of patient status. Conclusions Level of fatigue among psychiatric outpatients is high in patients with psychiatric illness, compared to levels measured in healthy volunteers. The Danish PROMIS-F-SF shows good psychometric properties in this combined sample of healthy adults and psychiatric patients with non-psychotic disorders and it is recommended as PRO measure for psychiatric populations. Examination of psychometric properties in patient populations with somatic disorder could be a natural next step.
Article
Efficient information exchange between government entities and citizens is crucial for effective governmental service delivery. However, e-government systems in developing countries like Botswana face challenges due to a lack of communication and integration among these systems. This case study addresses the interoperability challenges in Botswana's e-government systems by exploring and documenting the development of the e-government service-oriented interoperability framework (e-GSOIF). This framework integrates various technological and methodological approaches to improve service delivery and efficiency. It incorporates service-oriented architecture (SOA), event-driven architecture (EDA), ontologies, a refined software development lifecycle methodology, and the interoperability practical implementation support (IPIS) approach. The study pinpoints key factors impacting e-government system implementation and interoperability in Botswana through interviews, questionnaires, and observation. It also identifies essential technical components for E-Government Interoperability. The e-GSOIF framework is evaluated against the original IPIS framework using exploratory factor analysis and compatibility assessment with predefined functionality criteria, demonstrating its superiority. This paper targets government officials, IT specialists, researchers, and students interested in e-government services interoperability. It offers insights into advancing the landscape of e-government service delivery through an effective interoperability framework.
Article
This study evaluates AI ’s effectiveness in boosting real-time decision-making and supply chain agility in West African ports. Utilizing Structural Equation Modeling ( SEM ), data from 250 supply chain experts across several countries, including Ghana and Nigeria, were analyzed. Results indicate significant enhancements in supply chain agility, particularly through improved data processing speed, system integration, prediction accuracy, and user interface quality, with the latter having the most substantial impact. The study underscores the importance of user-friendly AI systems, supported by Dynamic Capabilities Theory, which facilitates organizational adaptability to market changes. Recommendations focus on developing AI systems with robust user interfaces and ensuring seamless integration with existing IT infrastructures. This research contributes to the literature by empirically demonstrating AI ’s role in improving operational adaptability and filling theoretical gaps, with a unique regional focus and methodological approach.
Article
Full-text available
Kur’ân-ı Kerîm’in öğrenilmesini destekleyen ve sağlayan dışsal etkinliklerin planlanması, düzenlenmesi, uygulanması ve değerlendirilmesi süreçlerinden oluşan Kur’ân-ı Kerîm öğretimi; örgün ve yaygın eğitim kurumlarında farklı yaş gruplarına ve seviyelerine göre yapılmaktadır. Kur’ân-ı Kerîm’in okunması ve öğretiminde belirlenen hedeflere ulaşılmasında öğretmenlerin/öğreticilerin mesleki öz yeterlikleri önemli rol oynamaktadır. Bu bağlamda Kur’ân-ı Kerîm öğretimi öz yeterlik inançlarını ölçmede kullanılabilecek geçerli ve güvenilir bir ölçek geliştirmeyi amaçlayan bu araştırma, tarama deseninde gerçekleştirilmiştir. Araştırmanın çalışma grubunu, Trabzon ilinde örgün eğitim kurumlarında görev yapan 570 Din Kültürü ve Ahlak Bilgisi öğretmeni oluşturmaktadır. Çalışma grubu ölçek geliştirme çalışmalarının önemli bir basamağı olan açımlayıcı ve doğrulayıcı faktör analizlerini farklı veri setleri üzerinde yapmak amacıyla bölünerek iki grup hâline getirilmiş ve her iki grubun normallik varsayımları sağlanmıştır. Birinci grup verileri üzerinde yapılan Açımlayıcı Faktör Analizi (AFA) sonucunda iki faktörlü bir yapı ortaya çıkmıştır. Faktörler; “Kur’ân-ı Kerîm’i Okuma” ve “Kur’ân-ı Kerîm’i Öğretme” olarak adlandırılmıştır. Faktörlerin madde yük değerleri 0.642 ile 0.889 arasında değişmektedir. Sırasıyla birinci faktör varyansın %36.239’unu, ikinci faktör varyansın %33.857’sini, ölçeğin tamamının ise varyansın %70.096’sını açıkladığı görülmüştür. İkinci grup veriler üzerinde yapılan Doğrulayıcı Faktör Analizinde (DFA), χ2/df: 2.635, RMSEA: 0.08; SRMR: 0.04; AGFI: 0.83; GFI: 0.88; CFI: 0.95; TLI: 0.94; NFI: 0.93 ve IFI: 0.95 uyum indeksleri elde edilmiştir. Ölçeğin madde toplam korelasyonları 0.533 ile 0.832 arasında değişmektedir. Ölçeğin %27 alt ve %27 üst grupların puan ortalamaları sonucunda elde edilen madde ayırt edicilik analizlerinin anlamlı olduğu (p
Article
Reading poses challenges for learners of English as a foreign language (EFL), as it requires strategic engagement with the text through an interactive meaning-making process. Self-regulated learning (SRL) training, which helps learners develop the ability to make strategic efforts to manage their reading process and maintain engagement in reading, has been increasingly used to assist EFL learners. However, one limitation of existing SRL training is the lack of interactive personalised support tailored to the specific needs of individual students. Recent developments in generative artificial intelligence (GenAI) may help address this limitation. This study explores how interactive personalised SRL support via a GenAI chatbot might affect university EFL learners' self-regulated strategy use and engagement in reading. Sixty-one Chinese EFL students from two classes at a university received a 45-min training session on SRL in reading and then engaged in a 12-week self-directed reading using an online reading platform embedded with SRL support. One class (the experimental group, N = 31) had access to the chatbot on the platform to support their self-regulated reading, while the other class (the control group, N = 30) received no chatbot assistance on the platform. Self-regulated reading strategy use and reading engagement were assessed through pre- and post-questionnaires, log data on the platform, and semi-structured interviews. It was found that the intervention significantly improved students' self-regulated reading strategy use and reading engagement, indicating the positive effect of GenAI-enabled interactive personalised SRL support. This study substantiates the value of interactive SRL support in the context of EFL reading.
Thesis
Full-text available
Bireyler ve toplumlar, pek çok değişim ve dönüşümle karşı karşıya kalmaktadırlar. 2011 yılında Endüstri 4.0 ile başlayan teknolojik değişim ve dönüşümün sonuncusu 2016 yılında Japonların ortaya attığı Toplum 5.0 kavramıdır. Temelinde teknolojik değişimlerin ve dönüşümlerin insanların yararına kullanılması vardır. Dijital dönüşüm ise daha çok üretim eksenli olup tüm iş süreçlerini, teknolojiyi ve insanı etkileyen bir kavramdır. Diğer yandan teknolojik gelişmeler yaşandıkça kültürel bazı değişikliklerin de beraberinde yaşanması kaçınılmazdır. Örgüt kültürü bağlamında düşünüldüğünde hem dijital dönüşümün hem de Toplum 5.0 anlayışının yerleşmesi için örgüt kültürünün değişmesi gerekmektedir. Bu araştırmanın amacı, Toplum 5.0 yapılanmasında dijital dönüşüm ve örgüt kültürü arasındaki etkileşimin incelenmesidir. Bu araştırmada yöntem olarak karma yöntemlerden açıklayıcı- sıralayıcı desen kullanılmıştır. Bu kapsamda çalışmanın örneklemini amaçlı örnekleme uygun olarak orta ve büyük işletme sahip ve üst düzey yöneticileri, akademisyenler ve kamu çalışanları oluşturmaktadır. Bu çerçevede 415 kişiye ulaşılmıştır. Araştırmanın nicel analiz kısmında frekans, açıklayıcı faktör, doğrulayıcı faktör, korelasyon, Yapısal Eşitlik Modeli ve ANOVA analizleri kullanılmıştır. Nitel analiz kısmında ise içerik analizi yöntemi kullanılarak 46 kişiyle yarı yapılandırılmış sorular sorularak görüşmeler gerçekleştirilmiştir. Bu kapsamda kod ilişkileri analizi uygulanmıştır. Tüm veriler, SPSS 25, AMOS 24 ve MAXQDA 20 programları kullanılarak analiz edilmiştir. Elde edilen bulgular doğrultusunda, nicel analiz kısmında dijital dönüşüm ve örgüt kültürü boyutlarının birbirlerini etkilediği, alt boyutlar olarak tüm boyutların yine birbirileri üzerinde bir etki oluşturduğu, ANOVA sonuçlarında gruplar arasında sadece dijital yetenekler alt boyutunda anlamlı bir farklılık olmadığı görülmüştür. Nitel analiz kısmında ise Toplum 5.0 ve alt boyutlarının hem dijital dönüşüm hem de örgüt kültürü ve alt boyutlarını etkilediği, Toplum 5.0 anlayışının yerleşmesi için dijital dönüşümün gerçekleşmesi ve örgüt kültürünün değişmesi gerektiği ortaya çıkmıştır.
Article
Full-text available
Uyum konusu gerek sosyal psikoloji gerekse sosyolojinin önemli konularından biridir. Yerleşik kültürlerde bile birçok faktörün etkili olduğu psiko-sosyal uyum olgusunu derinden etkileyen faktörlerden birisi de göç olayıdır. Literatürde az da olsa uyum konusunda işlevsel ölçek bulunmakla birlikte göçmenler üzerinde kullanılabilecek ölçekler ise yok denecek kadar az sayıdadır. Çalışmada görece uzun zaman farklı bir kültürde yaşayan göçmenlerin yaşadıkları yeni ortamlarına uyum düzeylerini ölçmek amacıyla geliştirilen ölçeğin psikometrik özelikleri sunulmuştur. Sırasıyla gerçekleştirilen ölçek geliştirme prosedürleri sonucunda beş boyutlu toplam 25 maddeden oluşan bir ölçek geliştirilmiştir. Açımlayıcı faktör analizi sonrası gerçekleştirilen doğrulayıcı faktör analizi ölçeğin beş faktörlü yapısını desteklemiş, yapılan güvenirlik analizleri de ölçeğin kullanılabilir güvenirlikte olduğunu göstermiştir.
Thesis
Full-text available
İşletmelerde örgütsel faaliyetlerin, hedeflerin, değerlerin, vizyon ve misyonun işletmede çalışan işgörenler tarafından kabul edilme ve benimsenme düzeyi işletme yönetiminin bir başarısıdır. Bu kabullenme, işgörenlerde işletme hakkında olumlu algı oluşmasına etkendir. İnsan kaynakları yönetimi açısından değerlendirildiğinde, örgütsel güvenin sağlandığı, yetenek yönetimine önem verildiği, işgörenlerin kariyer yönetiminin uygulandığı işletmelerde çalışan işgörenlerin performanslarının da yüksek olması beklenmektedir. İnsan kaynağının rekabette önemli bir bileşen haline gelmesi, insan kaynakları yönetimi alanındaki araştırmalara da yön vermiştir. İşletme yönetimi literatüründe güncel kavramlar olan kariyer yönetimi, yetenek yönetimi ve örgütsel güven değişkenlerinin birlikte işgören performansını nasıl etkilediği araştırmanın ilgi odağı olmuştur. Bu doğrultuda araştırma sonuçlarının, yetenek ve kariyer yönetimini başarıyla uygulayan ve örgütsel güveni sağlıklı bir zemine oturtmuş olan işletmelerde bu bileşenlerin işgören performans düzeyine nasıl etki ettiğini göstermesi ve dolaylı olarak işletme performansına yansıması açısından önemli olduğu düşünülmektedir. Araştırmanın temel amacı; “orta büyüklükteki işletmelerin kariyer ve yetenek yönetimi ile örgütsel güven uygulamalarının İşgören performansını etkileyip etkilemediğini” incelemektir. Bu amaca ulaşmak için tabakalı örneklem metodunun uygulandığı araştırmada; Akdeniz bölgesinde faaliyet gösteren, orta büyüklükteki 17 işletmede çalışan 565 işgörene anket yapılmış, kabul edilen 480 anketin verileri üzerinde yapılan açımlayıcı ve doğrulayıcı faktör analizi sonuçları sunulmuştur. Demografik değişkenlerden olan gelir düzeyinin işgören performansına etkisini ölçmek amacıyla tek yönlü ANOVA analizi yapılmıştır. Bağımsız değişkenlerin bağımlı değişkeni açıklama düzeylerini belirlemek amacıyla çoklu regresyon analizleri yapılmış ve araştırma hipotezleri test edilmiştir. Yapısal regresyon modeli ile araştırma modeli sınanmıştır. Yapısal regresyon modeli sonuçlarına göre; kariyer planlaması, kariyer yönetme, işletmeye çekme, eğitim ve geliştirme, çalışma arkadaşlarına güven ve işletmeye güvenin İşgören Performansı üzerinde anlamlı ve pozitif bir etkisi olduğu belirlenmiştir. Bununla birlikte demografik faktörlerden gelir değişkeninin kategorilerine göre işgören performansına verilen puan ortalamaları arasında anlamlı bir fark çıkması nedeniyle ücretin işgören performansına olumlu etkisi olduğu tespit edilmiştir. Seçme ve yerleştirme, elde tutma ve yöneticiye güvenin işgören performansını anlamlı bir şekilde etkilemediği görülmüştür. İşgören performansı değişkenin puan ortalamasının diğer değişkenlerin puan ortalamalarından daha yüksek olduğu, bu değişkenin diğer değişkenlere oranla işgücü piyasasını daha güçlü etkilediği sonucuna ulaşılmıştır. Değişkenler arasındaki korelasyon incelendiğinde en yüksek korelasyonun yöneticiye güven ile işletmeye güven boyutları arasında olduğu, bu boyutlar arasında pozitif yönde güçlü bir ilişki olduğu görülmüştür. Dolayısıyla işletmeye güvenin yöneticiye güvenle kazanılabileceği, işletmeye güvenin sağlanması için öncelikle yöneticilerin güven kazanma konusunda yeterli olması gerektiği düşünülmektedir. Çalışmada kurulan model, işgören performansının beşeri sermayenin kariyer ve yetenek yönetimi ile örgütsel güven yoluyla geliştirilebileceğini göstermektedir.
Article
Full-text available
Objective Lung cancer and its prolonged treatment are profoundly unsettling for patients and their family caregivers, and developing dyadic measures to alleviate their negative affectivity is pivotal. This study aimed to develop a complex intervention to alleviate dyadic psychological stress among patients with lung cancer and their family caregivers. Methods A stepwise multi-method study was conducted following the Medical Research Council framework. Three phases were adopted, namely: (1) a preparation phase, a systematic review was conducted to identify the evidence base, (2) a development phase, empirical data from a quantitative study and a qualitative study were integrated to identify effective components, and (3) a modification phase, an online Delphi survey was carried out to refine the intervention. Results The dyadic Mindfulness Self-Compassion intervention developed in this study consists of six weekly sessions. The key components of the intervention include: (1) getting along with cancer (introductory session targets illness perception), (2) practising mindful awareness (core session for mindfulness), (3) defining dyadic relationships and introducing self-compassion (core session for self-compassion), (4) promoting dyadic communication (maintenance session targets communication skills), (5) promoting dyadic coping (maintenance session targets coping skills), and (6) a summary session reviewing the rewards and challenges of dyadic adaptation named embracing the future. Conclusions An evidence-based, theory-driven, and culturally appropriate dyadic Mindfulness Self-Compassion intervention was developed for patients with lung cancer and their family caregivers. Future studies are warranted to pilot and evaluate the usability, feasibility, acceptability, satisfaction, and effectiveness of this complex intervention. Trial registration ClinicalTrial.gov NCT04795700.
Article
Full-text available
Background: Aggression is one of the important problems of psychosocial functioning, but it is also an area of physical and mental health among children and adolescents. The purpose of the present study was to examine the role of spiritual sensitivity as a mediator in the relationship between empathy and aggression in a group of school children and adolescents. Participants and procedure: The study included 281 children and adolescents (54% were girls) aged 9–14 years. The study procedure consisted of completing three questionnaires measuring spiritual sensitivity, empathy and aggression. The structural equation modeling using maximum likelihood estimation were used to determine the relationship between variables. Results: Our results suggest that spiritual sensitivity may mediate the relationship between empathy and aggression. Including spiritual sensitivity in the model reduced the negative relationship between the independent and dependent variables, indicating full mediation. Conclusions: In conclusion, the present study has provided some findings suggesting that spiritual sensitivity may indeed be one of the possible mechanisms by which religiosity leads to positive behavioral outcomes. The findings suggest that such internal factors may be important in leveling aggression and that focusing solely on environmental and situational influences may not fully capture individual differences in thinking, emotions and behavior.
Article
Full-text available
Introduction Research on gaming and gaming habits has predominantly focused on younger populations, particularly males. The main objective of this study was to analyze gender-based differences in gamer profiles, considering variables related to gaming habits and the gaming community. Methods A total of 180 Spanish university students currently engaged in video gaming (M = 21.51 years, SD = 3.09, 57.4% male) participated in the study by completing an online questionnaire addressing gaming characteristics such as the age of onset, gaming hours, motives of gaming, and perceived toxicity in the video gaming community. Results The results revealed statistically significant gender differences in the age of gaming initiation, weekly gaming hours, community toxicity, and several gaming motivations, including customization, cognitive challenge, violent gratification, and social interaction. Linear discriminant analysis identified that higher scores in the age of initiation and customization, along with lower scores in violent gratification and community toxicity, formed the combination of predictor variables that most strongly distinguished between genders. Conclusion Understanding these gender differences is essential for capturing current gaming trends and addressing the needs of diverse gamers. Finally, the potential clinical implications of these findings are discussed.
Article
Full-text available
Bu çalışmanın amacı Z kuşağı bireylerinin marka imajı algılarının satın alma davranışı üzerindeki etkisini ölçmeye yöneliktir. Şimdiye kadar var olan kuşaklardan ayrı olarak iletişim, telekomünikasyon ve teknoloji dünyası ile birlikte doğan Z kuşağı, geleceğin tüketici adayları olmalarından dolayı alışveriş alışkanlıklarının ve satın alma karar tarzlarının incelenmesi marka ve firmalar açısından büyük önem taşımaktadır. Bu sebeple araştırmanın amacı, hazır giyim sektörünün önemli bir potansiyeli olan Z kuşağının tüketici davranışlarının incelenmesi şeklinde belirlenmiştir. Araştırma Iğdır ilinde Google form üzerinden çevrim içi anket yöntemi ile toplam 552 katılımcı üzerinde gerçekleştirilmiştir. Araştırma kapsamında toplanan veriler SPPS 20 paket programı ile geçerlilik, güvenirlik, farklılık analizleri ve YEM Amos 21 paket programı ile yapısal eşitlik modellemesi, korelasyon ve yol analizleri yapılmıştır. Araştırma sonuçlarına göre bir markanın imaj düzeyi güçlendikçe tüketicilerin o markaya karşı satın alma davranışlarının pozitif yönlü artış gösterdiği tespit edilmiştir. Analiz sonuçları incelendiğinde bekâr ve kadın katılımcıların evli katılımcılara göre gider düzeylerinin daha düşük olması nedeniyle tercih ettikleri markaların imaj düzeylerinden etkilendikleri ve buna bağlı olarak satın alma düzeylerinin yüksek olduğu belirlenmiştir. Araştırma kapsamında elde edilen bir başka sonuç ise bireylerin gelirleri arttıkça marka imajı eğilimleri yükselmekte ve markaya karşı olan eğilimleri artmaktadır. Ayrıca demografik değişkenler açısından bireylerin satın alma tutumlarının etkilendiği sonucuna ulaşılmıştır. Araştırmada elde edilen bir diğer sonuca göre ise katılımcıların (n=552, %79,5’i) marka tercihlerinde reklamların bir etkisinin olmadığını belirtmişlerdir. Ulaşılan bu sonuçlara dayanarak firmaların pazarlama operasyonlarında geleneksel pazarlama yöntemleri yerine modern pazarlama yöntemlerini uygulamaları önerilmektedir.
Article
Full-text available
Studies that combine moderation and mediation are prevalent in basic and applied psychology research. Typically, these studies are framed in terms of moderated mediation or mediated moderation, both of which involve similar analytical approaches. Unfortunately, these approaches have important shortcomings that conceal the nature of the moderated and the mediated effects under investigation. This article presents a general analytical framework for combining moderation and mediation that integrates moderated regression analysis and path analysis. This framework clarifies how moderator variables influence the paths that constitute the direct, indirect, and total effects of mediated models. The authors empirically illustrate this framework and give step-by-step instructions for estimation and interpretation. They summarize the advantages of their framework over current approaches, explain how it subsumes moderated mediation and mediated moderation, and describe how it can accommodate additional moderator and mediator variables, curvilinear relationships, and structural equation models with latent variables.
Article
Full-text available
A non-arbitrary method for the identification and scale setting of latent variables in general structural equation modeling is introduced. This particular technique pro- vides identical model fit as traditional methods (e.g., the marker variable method), but it allows one to estimate the latent parameters in a nonarbitrary metric that re- flects the metric of the measured indicators. This technique, therefore, is particularly useful for mean and covariance structures (MACS) analyses, where the means of the indicators and latent constructs are of key interest. By introducing this alternative method of identification and scale setting, researchers are provided with an addi- tional tool for conducting MACS analyses that provides a meaningful and non- arbitrary scale for the estimates of the latent variable parameters. Importantly, this tool can be used with single-group single-occasion models as well as with multi- ple-group models, multiple-occasion models, or both. In this brief note, a non-arbitrary method for identification and scale setting of la- tent variables in general structural equation modeling (SEM) and, more specifi- cally, with mean and covariance structures (MACS) analyses, is introduced. In so doing, the two most common methods for identifying and scaling constructs are re- viewed and the strengths and weaknesses of the various approaches are discussed. For simplicity, demonstration focuses on the common SEM situation in which (a) constructs have multiple indicators, (b) most indicators load only on one construct (i.e., "simple structure"), and (c) each indicator has the same possible response scale (i.e., same range of possible outcomes). In other words, the discussion of identification and scale setting applies to rather unrestricted assumptions about the
Article
Full-text available
Although there are a variety of statistical methods available for the analysis of longitudinal panel data, two approaches are of particular historical importance: the autoregressive (simplex) model and the latent trajectory (curve) model. These two approaches have been portrayed as competing methodologies such that one approach is superior to the other. We argue that the autoregressive and trajectory models are special cases of a more encompassing model that we call the autoregressive latent trajectory (ALT) model. In this paper we detail the underlying statistical theory and mathematical identification of this model, and demonstrate the ALT model using two empirical data sets. The first reanalyzes a simulated repeated measures data set that was previously used to argue against the autoregressive model, and we illustrate how the ALT model can recover the true latent curve model. Second, we apply the ALT model to real family income data on N=3912 adults over a seven year period and find evidence for both autoregressive and latent trajectory processes. Extensions and limitations are discussed.
Article
Full-text available
The authors provide a basic set of guidelines and recommendations for information that should be included in any manuscript that has confirmatory factor analysis or structural equation modeling as the primary statistical analysis technique. The authors provide an introduction to both techniques, along with sample analyses, recommendations for reporting, evaluation of articles in The Journal of Educational Research using these techniques, and concluding remarks.
Article
Full-text available
The authors examined the methodologies of articles in teaching-and-learning research journals, published in 1994 and in 2004, and classified them as either intervention (based on researcher-manipulated variables) or nonintervention. Consistent with the findings of Hsieh et al., intervention research articles declined from 45% in 1994 to 33% in 2004. For nonintervention articles, the authors recorded the incidence of “causal” statements (e.g., if teachers/schools/parents did X, then student/child outcome Y would likely result). Nonintervention research articles containing causal statements increased from 34% in 1994 to 43% in 2004. It appears that at the same time intervention studies are becoming less prevalent in the teaching-and-learning research literature, researchers are more inclined to include causal statements in nonintervention studies.
Article
Full-text available
The present article responds to selected criticisms of some EPM editorial policies and Vacha-Haase’s “reliability generalization” meta-analytic methods. However, the treatment is more broadly a manifesto regarding the nature of score reliability and what are reasonable expectations for psychometric reporting practices in substantive inquiries. The consequences of misunderstandings of score reliability are explored. It is suggested that paradigmatic misconceptions regarding psychometric issues feed into a spiral of presumptions that measurement training is unnecessary for doctoral students, which then in turn further reinforces misunderstandings of score integrity issues.
Article
Full-text available
Across a variety of disciplines and areas of inquiry, reliable and valid measures are a cornerstone of quality research. This is the case because to have confidence in the findings of our studies, we must first have confidence in the quality of our measures. This article briefly reviews the literature on scale development and provides an empirical demonstration of the scale development process. The example considered is the development and validation of a condom influence strategy questionnaire-short form (CISQ-S), a scale to measure ways individuals persuade their partners to use condoms. A special focus is put on the unique contribution that structural equation modeling techniques, particularly confirmatory factor analysis, bring to scale development. Latent variable modeling and its applications to scale development are also considered. Suggestions and implications for scale developers are discussed.
Article
Full-text available
The goals of this article are twofold: (a) briefly highlight the merits of residual centering for representing interaction and powered terms in standard regression contexts (e.g., Lance, 1988), and (b) extend the residual centering procedure to represent latent variable interactions. The proposed method for representing latent variable interactions has potential advantages over extant procedures. First, the latent variable interaction is derived from the observed covariation pattern among all possible indicators of the interaction. Second, no constraints on particular estimated parameters need to be placed. Third, no recalculations of parameters are required. Fourth, model estimates are stable and interpretable. In our view, the orthogonalizing approach is technically and conceptually straightforward, can be estimated using any structural equation modeling software package, and has direct practical interpretation of parameter estimates. Its behavior in terms of model fit and estimated standard errors is very reasonable, and it can be readily generalized to other types of latent variables where nonlinearity or collinearity are involved (e.g., powered variables).
Article
Full-text available
The purpose of this article is to provide researchers, editors, and readers with a set of guidelines for what to expect in an article using logistic regression techniques. Tables, figures, and charts that should be included to comprehensively assess the results and assumptions to be verified are discussed. This article demonstrates the preferred pattern for the application of logistic methods with an illustration of logistic regression applied to a data set in testing a research hypothesis. Recommendations are also offered for appropriate reporting formats of logistic regression results and the minimum observation-to-predictor ratio. The authors evaluated the use and interpretation of logistic regression presented in 8 articles published in The Journal of Educational Research between 1990 and 2000. They found that all 8 studies met or exceeded recommended criteria.
Article
Full-text available
Factor structures obtained by exploratory factor analysis (EFA) often turn out to fit poorly in confirmative follow-up studies. In the present study, the authors assessed the extent to which results obtained in EFA studies can be replicated by confirmatory factor analysis (CFA) in the same sample. More specifically, the authors used CFA to test three different factor models on several correlation matrices of exploratively obtained factor structures that were reported in the literature. The factor models varied with respect to the role of the smaller factor pattern coefficients. Results showed that confirmatory factor models in which all low EFA pattern coefficients were fixed to zero fitted especially poorly. The authors conclude that it may be justified to use a less constrained model when testing a factor model by allowing some correlation among the factors and some of the lower factor pattern coefficients to differ from zero.
Article
Full-text available
This article combines procedures for single-level mediational analysis with multilevel modeling techniques in order to appropriately test mediational effects in clustered data. A simulation study compared the performance of these multilevel mediational models with that of single-level mediational models in clustered data with individual- or group-level initial independent variables, individual- or group-level mediators, and individual level outcomes. The standard errors of mediated effects from the multilevel solution were generally accurate, while those from the single-level procedure were downwardly biased, often by 20% or more. The multilevel advantage was greatest in those situations involving group-level variables, larger group sizes, and higher intraclass correlations in mediator and outcome variables. Multilevel mediational modeling methods were also applied to data from a preventive intervention designed to reduce intentions to use steroids among players on high school football teams. This example illustrates differences between single-level and multilevel mediational modeling in real-world clustered data and shows how the multilevel technique may lead to more accurate results. Mediational analysis is a method that can help researchers understand the mechanisms underlying the phenomena they study. The basic mediational framework involves a three variable system in which an initial independent variable affects a mediational variable, which, in turn, affects an outcome variable (Baron & Kenny, 1986). The aim of mediational analysis is to determine whether the relation between the initial variable and the outcome is due, wholly or in part, to the mediator. Mediational analysis is applicable across a wide range of experimental and non-experimental
Article
Full-text available
Fit indexes were compared with respect to a specific type of model misspecification. Simple structure was violated with some secondary loadings that were present in the true models that were not specified in the estimated models. The c2 test, Comparative Fit Index, Goodness-of-Fit Index, Incremental Fit Index, Nonnormed Fit Index, root mean squared error of approximation, standardized root mean square residual, and the c2/df values were investigated. Simulated data sets with 3 sample sizes (250, 500, and 1,000 cases), 4 levels of main loadings (.40,. 50,. 60, and. 80), 2 numbers of factors (4, 8), and 2 types of association matrix (covariance, correlation) were the basis for maximum likelihood estimation of orthogonal and oblique factor models. Some correlations between fit indexes were low. Moreover, small distortions from simple structure did not lead to misfit in the RMSEA and SRMR, but they often led to misfit in the incremental fit indexes. This result may be of interest for research on personality traits, where small violations of simple structure are very common.
Article
Full-text available
This simulation study demonstrates how the choice of estimation method affects indexes of fit and parameter bias for different sample sizes when nested models vary in terms of specification error and the data demonstrate different levels of kurtosis. Using a fully crossed design, data were generated for 11 conditions of peakedness, 3 conditions of misspecification, and 5 different sample sizes. Three estimation methods (maximum likelihood [ML], generalized least squares [GLS], and weighted least squares [WLS]) were compared in terms of overall fit and the discrepancy between estimated parameter values and the true parameter values used to generate the data. Consistent with earlier findings, the results show that ML compared to GLS under conditions of misspecification provides more realistic indexes of overall fit and less biased parameter values for paths that overlap with the true model. However, despite recommendations found in the literature that WLS should be used when data are not normally distributed, we find that WLS under no conditions was preferable to the 2 other estimation procedures in terms of parameter bias and fit. In fact, only for large sample sizes (N = 1,000 and 2,000) and mildly misspecified models did WLS provide estimates and fit indexes close to the ones obtained for ML and GLS. For wrongly specified models WLS tended to give unreliable estimates and over-optimistic values of fit.
Article
Full-text available
We surveyed a national sample of U.S. undergraduate psychology programs regarding the structure and content of statistical training. Results revealed considerable diversity in approaches and offerings. Contemporary trends in data analysis (e.g., power and effect size analysis, confidence interval estimation, general linear model approaches) as well as measurement issues appear to receive relatively little attention in the core sequence. Respondents tended to view such topics as appropriate for more advanced courses, which they said were infrequently required. We discuss options for addressing issues of course sequencing, content focus, and advanced-level offerings in the major.
Article
Full-text available
In previous research (Hu & Bentler, 1998, 1999), 2 conclusions were drawn: stan-dardized root mean squared residual (SRMR) was the most sensitive to misspecified factor covariances, and a group of other fit indexes were most sensitive to mis-specified factor loadings. Based on these findings, a 2-index strategy—that is, SRMR coupled with another index—was proposed in model fit assessment to detect poten-tial misspecification in both the structural and measurement model parameters. Based on our reasoning and empirical work presented in this article, we conclude that SRMR is not necessarily most sensitive to misspecified factor covariances (structural model misspecification), the group of indexes (TLI, BL89, RNI, CFI, Gamma hat, Mc, or RMSEA) are not necessarily more sensitive to misspecified factor loadings (measurement model misspecification), and the rationale for the 2-index presenta-tion strategy appears to have questionable validity. The assessment of model fit in structural equation modeling (SEM) has long been a thorny issue in SEM application. As a result, the issues related to model fit as-sessment in SEM analysis have been at the forefront of theoretical and empirical research over the years. Research in this area has focused on different issues con-cerning the use and interpretation of model fit indexes. Studies typically examined the performance characteristics of different fit indexes under different data condi-STRUCTURAL EQUATION MODELING, 12(3), 343–367 Copyright © 2005, Lawrence Erlbaum Associates, Inc.
Article
Full-text available
Model evaluation is one of the most important aspects of structural equation modeling (SEM). Many model fit indices have been developed. It is not an exaggeration to say that nearly every publication using the SEM methodology has reported at least one fit index. Most fit indices are defined through test statistics. Studies and interpretation of fit indices commonly assume that the test statistics follow either a central chi-square distribution or a noncentral chi-square distribution. Because few statistics in practice follow a chi-square distribution, we study properties of the commonly used fit indices when dropping the chi-square distribution assumptions. The study identifies two sensible statistics for evaluating fit indices involving degrees of freedom. We also propose linearly approximating the distribution of a fit index/statistic by a known distribution or the distribution of the same fit index/statistic under a set of different conditions. The conditions include the sample size, the distribution of the data as well as the base-statistic. Results indicate that, for commonly used fit indices evaluated at sensible statistics, both the slope and the intercept in the linear relationship change substantially when conditions change. A fit index that changes the least might be due to an artificial factor. Thus, the value of a fit index is not just a measure of model fit but also of other uncontrollable factors. A discussion with conclusions is given on how to properly use fit indices.
Article
Full-text available
Confirmatory factor analysis (CFA) is a statistical procedure frequently used to test the fit of data to measurement models. Published CFA studies typically report factor pattern coefficients. Few reports, however, also present factor structure coefficients, which can be essential for the accurate interpretation of CFA results. The interpreta-tion errors that can arise when CFA results are interpreted without considering struc-ture coefficients are described, and some examples from current literature illustrating these errors are also presented. The close association between factor analysis and measurement has been previ-ously noted (cf. Thompson & Daniel, 1996). Thus Nunnally (1978) long ago sug-gested that "factor analysis is intimately involved with questions of validity … Factor analysis is at the heart of the measurement of psychological constructs" (pp. 112–113). Both exploratory factor analysis (EFA; cf. Gorsuch, 1983) and confirmatory factor analysis (CFA; cf. Byrne, 1994) are frequently employed in measurement studies. Because CFA directly tests the fit of theoretically or empirically grounded models to data, these models are especially useful, for at least three reasons. First, CFA allows several rival models to be fit to data, and consequently better honors the role of falsification within scientific inquiry (Popper, 1962). Falsifica-STRUCTURAL EQUATION MODELING, 10(1), 142–153 Copyright © 2003, Lawrence Erlbaum Associates, Inc.
Article
Full-text available
Modeling strategies are subject to debate for virtually all statistical procedures. Witness the sharp disagreements over stepwise regression, the interpretation of clusters in cluster analysis, or the identification of outliers and influential points. The largely objective basis of statistical algorithms does not remove the need for human judgment in their implementation. So it is not surprising that the use of structural equation models is subject to disputes over the best way to formulate and test models. Though I must admit considerable scepticism about whether it is possi-ble to have a single generic strategy that would prove optimal over all substantive areas and types of structural equation models, articles and discussions such as those of Hayduk and Glaser (2000) and Mulaik (1998) are very helpful in that they bring out the merits and limits of the alternative procedures. The options that are the focus of their discussions are (a) the one-step procedure and (b) the four-step approach. In a sense, we could see the one-step procedure as there at the birth of contemporary structural equation models. One of the attractive features of structural equation models was the ability to simultaneously model the latent variable and the measurement models in one step. 1 Defenders of this original practice include Hayduk (1987, 1996) and Fornell and Yi (1992). More recently, Mulaik (1998) has advocated a four-step method that is the subject of the Hayduk and Glaser (2000) article. 1 I depart from the current practice of referring to the latent variable model as the "structural" model. Such a labeling suggests that the measurement model is not structural and that only the latent variable model involves structural parameters (Bollen, 1989, p.11). Using the term latent variable model can avoid this confusion.
Article
Full-text available
We examine the controversial practice of using parcels of items as manifest variables in structural equation modeling (SEM) procedures. After detailing arguments pro and con, we conclude that the unconsidered use of parcels is never warranted, while, at the same time, the considered use of parcels cannot be dismissed out of hand. In large part, the decision to parcel or not depends on one's philosophical stance regard- ing scientific inquiry (e.g., empiricist vs. pragmatist) and the substantive goal of a study (e.g., to understand the structure of a set of items or to examine the nature of a set of constructs). Prior to creating parcels, however, we recommend strongly that in- vestigators acquire a thorough understanding of the nature and dimensionality of the items to be parceled. With this knowledge in hand, various techniques for creating parcels can be utilized to minimize potential pitfalls and to optimize the measure- ment structure of constructs in SEM procedures. A number of parceling techniques are described, noting their strengths and weaknesses.
Article
Full-text available
For journal editors, reviewers, and readers of research articles, structural equation model (SEM) fit has recently become a confusing and contentious area of evaluative methodology. Proponents of two kinds of approaches to model fit can be identified: those who adhere strictly to the result from a null hypothesis significance test, and those who ignore this and instead index model fit as an approximation function. Both have principled reasons for their respective course of action. This paper argues that the chi-square exact-fit test is the only substantive test of fit for SEM, but, its sensitivity to discrepancies from expected values at increasing sample sizes can be highly problematic if those discrepancies are considered trivial from an explanatory-theory perspective. On the other hand, suitably scaled indices of approximate fit do not possess this sensitivity to sample size, but neither are they “tests” of model fit. The proposed solution to this dilemma is to consider the substantive “consequences” of accepting one explanatory model over another in terms of the predictive accuracy of theory-relevant-criteria. If there are none to be evaluated, then it is proposed that no scientifically worthwhile distinction between “competing” models can thus be made, which of course begs the question as to why such a SEM application was undertaken in the first place.
Article
Full-text available
Data transformations are commonly used tools that can serve many functions in quantitative analysis of data. The goal of this paper is to focus on the use of three data transformations most commonly discussed in statistics texts (square root, log, and inverse) for improving the normality of variables. While these are important options for analysts, they do fundamentally transform the nature of the variable, making the interpretation of the results somewhat more complex. Further, few (if any) statistical texts discuss the tremendous influence a distribution's minimum value has on the efficacy of a transformation. The goal of this paper is to promote thoughtful and informed use of data transformations.
Article
Full-text available
The use of significance tests in science has been debated from the invention of these tests until the present time. Apart from theoretical critiques on their appropriateness for evaluating scientific hypotheses, significance tests also receive criticism for inviting mi- sinterpretations. We presented six common misinterpretations to psychologists who work in German universities and found out that they are still surprisingly widespread - even among instructors who teach statistics to psychology students. Although these mi- sinterpretations are well documented among students, until now there has been little research on pedagogical methods to remove them. Rather, they are considered "hard facts" that are impervious to correction. We discuss the roots of these misinterpretations and propose a pedagogical concept to teach significance tests, which involves explaining the meaning of statistical significance in an appropriate way.
Article
Full-text available
Reporting practices in 194 confirmatory factor analysis studies (1,409 factor models) published in American Psychological Association journals from 1998 to 2006 were reviewed and compared with established reporting guidelines. Three research questions were addressed: (a) how do actual reporting practices compare with published guidelines? (b) how do researchers report model fit in light of divergent perspectives on the use of ancillary fit indices (e.g., L.-T. Hu & P. M. Bentler, 1999; H. W. Marsh, K.-T., Hau, & Z. Wen, 2004)? and (c) are fit measures that support hypothesized models reported more often than fit measures that are less favorable? Results indicate some positive findings with respect to reporting practices including proposing multiple models a priori and near universal reporting of the chi-square significance test. However, many deficiencies were found such as lack of information regarding missing data and assessment of normality. Additionally, the authors found increases in reported values of some incremental fit statistics and no statistically significant evidence that researchers selectively report measures of fit that support their preferred model. Recommendations for reporting are summarized and a checklist is provided to help editors, reviewers, and authors improve reporting practices.
Article
Full-text available
A review of the literature suggests that few studies use formative indicator measurement models, even though they should. Therefore, the purpose of this research is to (a) discuss the distinction between formative and reflective measurement models, (b) develop a set of conceptual criteria that can be used to determine whether a construct should be modeled as having formative or reflective indicators, (c) review the marketing literature to obtain an estimate of the extent of measurement model misspecification in the field, (d) estimate the extent to which measurement model misspecification biases estimates of the relationships between constructs using a Monte Carlo simulation, and (e) provide recommendations for modeling formative indicator constructs. Copyright 2003 by the University of Chicago.
Article
Full-text available
Whereas measures of explained variance in a regression and an equation of a recursive structural equation model can be simply summarized by a standard R2 measure, this is not possible in nonrecursive models in which there are reciprocal interdependencies among variables. This article provides a general approach to defining variance explained in latent dependent variables of nonrecursive linear structural equation models. A new method of its estimation, easily implemented in EQS or LISREL and available in EQS 6, is described and illustrated.
Article
Full-text available
This study examined the role of acculturation and its direct and indirect impact on depressive symptom severity through various correlates, including socioeconomic status (SES), stress, social support, personality negativity, and physical health perception. Using structural equation modeling, the proposed model was tested with 983 employed Chinese Americans from a representative community sample, the majority of whom were immigrants. The results demonstrated that acculturation, correlated with SES, contributed to depressive symptom severity only through indirect pathways. Higher acculturation was found associated with higher stress that in turn contributed to more elevated depressive symptoms. On the other hand, higher acculturation was also found strongly correlated with higher SES, which was associated with lower depressive symptoms directly or indirectly through several mediators. Better support, lower personality negativity, better health perception, and lower stress were found mediating the relationship between higher SES and lower depressive symptom severity. The simultaneous multigroup analysis showed that the final model was comparable for both men and women with very few differences.
Article
Full-text available
Principles for reporting analyses using structural equation modeling are reviewed, with the goal of supplying readers with complete and accurate information. It is recommended that every report give a detailed justification of the model used, along with plausible alternatives and an account of identifiability. Nonnormality and missing data problems should also be addressed. A complete set of parameters and their standard errors is desirable, and it will often be convenient to supply the correlation matrix and discrepancies, as well as goodness-of-fit indices, so that readers can exercise independent critical judgment. A survey of fairly representative studies compares recent practice with the principles of reporting recommended here.
Article
Multilevel linear models (MLMs) provide a powerful framework for analyzing data collected at nested or non-nested levels, such as students within classrooms. The current article draws on recent analytical and software advances to demonstrate that a broad class of MLMs may be estimated as structural equation models (SEMs). Moreover, within the SEM approach it is possible to include measurement models for predictors or outcomes, and to estimate the mediational pathways among predictors explicitly, tasks which are currently difficult with the conventional approach to multilevel modeling. The equivalency of the SEM approach with conventional methods for estimating MLMs is illustrated using empirical examples, including an example involving both multiple indicator latent factors for the outcomes and a causal chain for the predictors. The limitations of this approach for estimating MLMs are discussed and alternative approaches are considered.
Article
R is free, open-source, cooperatively developed software that implements the S statistical programming language and computing environment. The current capabilities of R are extensive, and it is in wide use, especially among statisticians. The sem package provides basic structural equation modeling facilities in R, including the ability to fit structural equations in observed variable models by two-stage least squares, and to fit latent variable models by full information maximum likelihood assuming multinormality. This article briefly describes R, and then proceeds to illustrate the use of the tsls and sem functions in the sem package. The article also demonstrates the integration of the sem package with other facilities available in R, for example for computing polychoric correlations and for bootstrapping.
Article
Exploratory factor analysis (EFA) is a frequently used multivariate analysis technique in statistics. Jennrich and Sampson (1966)19. Jennrich , R. I. and Sampson , P. F. 1966. Rotation to simple loadings.. Psychometrika, 31: 313–323. [CrossRef], [PubMed], [Web of Science ®]View all references solved a significant EFA factor loading matrix rotation problem by deriving the direct Quartimin rotation. Jennrich was also the first to develop standard errors for rotated solutions, although these have still not made their way into most statistical software programs. This is perhaps because Jennrich's achievements were partly overshadowed by the subsequent development of confirmatory factor analysis (CFA) by Jöreskog (1969)20. Jöreskog , K. G. 1969. A general approach to confirmatory maximum-likelihood factor analysis.. Psychometrika, 34: 183–202. [CrossRef], [Web of Science ®]View all references. The strict requirement of zero cross-loadings in CFA, however, often does not fit the data well and has led to a tendency to rely on extensive model modification to find a well-fitting model. In such cases, searching for a well-fitting measurement model may be better carried out by EFA (Browne, 20017. Browne , M. W. 2001. An overview of analytic rotation in exploratory factor analysis.. Multivariate Behavioral Research, 36: 111–150. [Taylor & Francis Online], [Web of Science ®]View all references). Furthermore, misspecification of zero loadings usually leads to distorted factors with over-estimated factor correlations and subsequent distorted structural relations. This article describes an EFA-SEM (ESEM) approach, where in addition to or instead of a CFA measurement model, an EFA measurement model with rotations can be used in a structural equation model. The ESEM approach has recently been implemented in the Mplus program. ESEM gives access to all the usual SEM parameters and the loading rotation gives a transformation of structural coefficients as well. Standard errors and overall tests of model fit are obtained. Geomin and Target rotations are discussed. Examples of ESEM models include multiple-group EFA with measurement and structural invariance testing, test–retest (longitudinal) EFA, EFA with covariates and direct effects, and EFA with correlated residuals. Testing strategies with sequences of EFA and CFA models are discussed. Simulated and real data are used to illustrate the points.
Article
Research supports a hierarchical factor structure of intelligence that is consistent with the second-order factor model proposed by Gustafsson in which five first-order factors yield a single second-order factor of General Intelligence (g). Gustafsson’s model was tested with structural equation modeling via the Ball Aptitude Battery (BAB), a measure of aptitudes and vocational interests. This study focuses on the tests from the BAB that are believed to measure various aspects of intelligence: Numerical Computation, Numerical Reasoning, Inductive Reasoning, Analytical Reasoning, Paper Folding, Idea Fluency, Idea Generation, Vocabulary, Associative Memory, Auditory Memory, Clerical, and Writing Speed. Results indicate that the factor structure of the BAB is consistent with Gustafsson’s second-order factor model of intelligence. Implications of this finding are discussed.
Article
This article establishes a new criterion for the identification of recursive linear mod- els in which some errors are correlated. We show that identification is ensured as long as error correlation does not exist between a cause and its direct effect; no restrictions are imposed on errors associated with indirect causes.
Article
Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the conditional relations is often a tedious and error-prone task. This article provides an overview of methods used to probe interaction effects and describes a unified collection of freely available online resources that researchers can use to obtain significance tests for simple slopes, compute regions of significance, and obtain confidence bands for simple slopes across the range of the moderator in the MLR, HLM, and LCA contexts. Plotting capabilities are also provided.
Article
The Programme for International Student Assessment comparative study of reading performance among 15-year-olds is reanalyzed using statistical procedures that allow the full complexity of the data structures to be explored. The article extends existing multilevel factor analysis and structural equation models and shows how this can extract richer information from the data and provide better fits to the data. It shows how these models can be used fully to explore the dimensionality of the data and to provide efficient, single-stage models that avoid the need for multiple imputation procedures. Markov Chain Monte Carlo methodology for parameter estimation is described.
Article
Recently, there has been increased interest in tests of measurement equivalence/ invariance (ME/I). This study uses simulated data with known properties to assess the appropriateness, similarities, and differences between confirmatory factor analysis and item response theory methods of assessing ME/I. Results indicate that although neither approach is without flaw, the item response theory–based approach seems to be better suited for some types of ME/I analyses.
Article
Measurement invariance is usually tested using Multigroup Confirmatory Factor Analysis, which examines the change in the goodness-of-fit index (GFI) when cross-group constraints are imposed on a measurement model. Although many studies have examined the properties of GFI as indicators of overall model fit for single-group data, there have been none to date that examine how GFIs change when between-group constraints are added to a measurement model. The lack of a consensus about what constitutes significant GFI differences places limits on measurement invariance testing. We examine 20 GFIs based on the minimum fit function. A simulation under the two-group situation was used to examine changes in the GFIs (ΔGFIs) when invariance constraints were added. Based on the results, we recommend using Δcomparative fit index, ΔGamma hat, and ΔMcDonald's Noncentrality Index to evaluate measurement invariance. These three ΔGFIs are independent of both model complexity and sample size, and are not correlated with the overall fit measures. We propose critical values of these ΔGFIs that indicate measurement invariance.
Article
Two simulation studies were conducted to investigate the effects of the practice of item parceling. In Study 1, unidimensional sets of normally and nonnormally distrib- uted item-level data were categorized into 2-, 3-, and 4-item parcels. Analyses re- vealed that the use of item parcels resulted in better fitting solutions, as measured by the root mean squared error of approximation (RMSEA), comparative fit index (CFI), and chi-square test, when items had a unidimensional structure. Parceled solu- tions also resulted in less bias in estimates of structural parameters under these condi- tions than did solutions based on the individual items. In Study 2 the issue of whether the use of item parceling could mask a known multidimensional factor structure among a set of items was investigated. Results indicated that certain types of item parceling can obfuscate a multidimensional factor structure in such a way that ac- ceptable values of fit indexes are found for a misspecified solution. In addition, par- celing under these conditions was found to result in bias in the estimates of structural parameters. Although parceling can ameliorate the effects of coarsely categorized and nonnormally distributed item-level data when the items are unidimensional, the use of parceling with items that are multidimensional or for which the factor structure is unknown cannot be recommended.
Article
This study examines the growth and development of structural equation modeling (SEM) from the years 1994 to 2001. The synchronous development and growth of the Structural Equation Modeling journal was also examined. Abstracts located on PsycINFO were used as the primary source of data. The major results of this investi-gation were clear: (a) The number of journal articles concerned with SEM increased; (b) the number of journals publishing these articles increased; (c) SEM acquired he-gemony among multivariate techniques; and (d) Structural Equation Modeling be-came the primary source of publication for technical developments in SEM. Structural equation modeling (SEM) has become the preeminent multivariate technique, and the Structural Equation Modeling journal has become the preemi-nent place for the publication of developments and applications in SEM. To work-ers in SEM, this statement will come as no surprise, nor invite controversy. To oth-ers not as committed or as familiar with SEM, this statement may appear dubious. To them, this article is intended. The purpose of this study is to show how both structural equation modeling as a technique and Structural Equation Modeling as a journal, have simultaneously grown since the journal's inception in 1994. This contemporaneous development is no mere coincidence: Both the technique and the journal have given strength and momentum to each other.
Article
The effectiveness of various analytical formulas for estimating R 2 shrinkage in multiple regression analysis was investigated. Two categories of formu-las were identified: estimators of the squared population multiple correlation coeffi-cient (p 2) and those of the squared population cross-validity coefficient (pc 2). The authors conducted a Monte Carlo experiment to investigate the effectiveness of the analytical formulas for estimating R 2 shrinkage, with 4 fully crossed factors (squared population multiple correlation coeMcient, number of predictors, sample size, and degree of multicollinearity) and 500 replications in each cell. The results indicated that the most widely used Wherry formula (in both SAS and SPSS) is probably not the most effective analytical formula for estimating p 2 . Instead, the Pratt formula and the Browne formula outperformed other analytical formulas in estimating p 2 and pc 2 , respectively.
Article
A Monte Carlo simulation examined the performance of 4 missing data methods in structural equation models: full information maximum likelihood (FIML), listwise deletion, pairwise deletion, and similar response pattern imputation. The effects of 3 independent variables were examined (factor loading magnitude, sample size, and missing data rate) on 4 outcome measures: convergence failures, parameter estimate bias, parameter estimate efficiency, and model goodness of fit. Results indicated that FIML estimation was superior across all conditions of the design. Under ignorable missing data conditions (missing completely at random and missing at random), FIML estimates were unbiased and more efficient than the other methods. In addition, FIML yielded the lowest proportion of convergence failures and provided near-optimal Type 1 error rates across both simulations.
Article
Structural equation modeling (SEM) is a viable multivariate tool used by communication researchers for the past quarter century. Building off Cappella (1975) as well as McPhee and Babrow (1987), this study summarizes the use of this technique from 1995–2000 in 37 communication-based academic journals. We identify and critically assess 3 unique methods for testing structural relationships via SEM in terms of the specification, estimation, and evaluation of their respective structural equation models. We provide general guidelines for the use of SEM and make recommendations concerning latent variable models, sample size, reporting parameter estimates, model fit statistics, cross-sectional data, univariate normality, cross-validation, nonrecursive modeling, and the decomposition of effects (direct, indirect, and total).
Article
A model explaining several causes and consequences of negative teacher–pupil relationships was developed. Data from 109 teachers and 946 high school pupils was analyzed using path analysis. The results suggest that teachers who prefer a custodial approach of controlling pupils, who have lower morale due to school climate conditions and who are less likely to burn out, tend to adopt conflict-inducing attitudes towards pupils. The results also demonstrate a high incidence of educational, psychological and somatic complaints in students whose characterized teachers are perceived as more hostile in their attitude towards pupils. Implications of these findings are discussed.
Article
Formative measurement models were first introduced in the literature more than forty years ago and the discussion about their methodological contribution has been increasing since the 1990s. However, the use of formative indicators for construct measurement in empirical studies is still scarce. This paper seeks to encourage the thoughtful application of formative models by (a) highlighting the potential consequences of measurement model misspecification, and (b) providing a state-of-the art review of key issues in the formative measurement literature. For the former purpose, this paper summarizes findings of empirical studies investigating the effects of measurement misspecification. For the latter purpose, the article merges contributions in the psychology, management, and marketing literatures to examine a variety of issues concerning the conceptualization, estimation, and validation of formative measurement models. Finally, the article offers some suggestions for future research on formative measurement.
Article
Despite intensive discussions about customer equity, little research addresses how to manage customer equity from a firm's perspective. Recent literature proposes various concepts of customer equity management but does not feature an empirical study that identifies and quantifies activities that aim explicitly to maximize customer equity. In the current study, the authors develop a formative measurement instrument for customer equity management as a second-order construct that indicates how intensively firms orient their customer management toward customer value and equity. The study presents a complete process for conceptualizing and operationalizing a formative second-order construct, including a thorough literature review, intensive qualitative research, and a quantitative study with 92 customer equity managers. On the basis of this process, the authors model customer equity management as a function of three formative dimensions – customer equity analysis, customer equity strategy, and customer equity actions – measured by several formative indicators. The resulting formative operationalization satisfies the criteria for evaluating formative indexes.
Article
Suppressor variables are well known in the context of multiple regression analysis. Using several examples, the authors demonstrate that the different forms of the suppressor phenomenon described in the literature occur not only in prediction equations but also in the explanatory use of multiple regression, including structural equations models. Moreover, they show that the probability of their occurrence is relatively high in models with latent variables, in which the suppressed variable is corrected for measurement errors. Special attention will be paid to the two-wave model since this is particularly liable to the suppressor phenomenon. The occurrence of suppression in structural equations models is usually not foreseen and confronts researchers with problems of interpretation. The authors discuss definitions of the suppressor phenomenon, show how the unwary researcher can be warned against it, and present guidelines for the interpretation of the results
Article
We introduce a new power transformation family which is well defined on the whole real line and which is appropriate for reducing skewness and to approximate normality. It has properties similar to those of the Box–Cox transformation for positive variables. The large&hyphen;sample properties of the transformation are investigated in the contect of a single random sample.
Article
In the context of structural equation modeling, a general interaction model with multiple latent interaction effects is introduced. A stochastic analysis represents the nonnormal distribution of the joint indicator vector as a finite mixture of normal distributions. The Latent Moderated Structural Equations (LMS) approach is a new method developed for the analysis of the general interaction model that utilizes the mixture distribution and provides a ML estimation of model parameters by adapting the EM algorithm. The finite sample properties and the robustness of LMS are discussed. Finally, the applicability of the new method is illustrated by an empirical example.
Article
This chapter presents a review of applications of structural equation modeling (SEM) published in psychological research journals in recent years. We focus first on the variety of research designs and substantive issues to which SEM can be applied productively. We then discuss a number of methodological problems and issues of concern that characterize some of this literature. Although it is clear that SEM is a powerful tool that is being used to great benefit in psychological research, it is also clear that the applied SEM literature is characterized by some chronic problems and that this literature can be considerably improved by greater attention to these issues.
Article
Quality of life (QOL) is presented as a global, unidimensional, and subjective assessment of one's life. This study examined the impact of perceived health status, hope, and optimism on QOL in 93 women after suffering a cardiac event. Construct validity was examined by estimating a model where QOL was measured with four indicators, and perceived health was measured with the SF-36 Health Survey. Hope was measured with the Herth Hope Index and dispositional optimism was measured with the Life Orientation Test. The unidimensionality of QOL and its response to health status, hope, and optimism were tested. Fit indices suggested that the theoretical relations posited were compatible with the data, (chi 2(42) = 44.125, p = .382, RMSEA = .0001, GFI = .942). The model explained 66% of the variance in QOL. Modeling suggested the presence of a complex latent concept composed of hope and optimism that influenced QOL.