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A Beginner's Guide To Structural Equation Modeling

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... DFA ile ölçeğin faktör ve madde yapısının uygunluğu değerlendirilmiştir. Ölçek modelinin doğrulanması için, faktörlerdeki tüm maddelerin istatistiksel olarak anlamlı bir şekilde yerleşmesi ve tüm maddelerin Path katsayılarının pozitif olması önerilmektedir (31). Ölçeğin güvenirliğinin değerlendirilmesinde iç tutarlılığı temsil eden Cronbach alfa ve McDonald omega katsayıları hesaplanmaktadır. ...
... Uyum İyiliği İndeksi (Goodness Fit Index, GFI), Karşılaştırmalı Uyum İndeksi (Comparative Fit Index, CFI), Düzeltilmiş İyilik Uyum İndeksi (Adjusted Goodness of Fit Index, AGFI), Tucker-Lewis İndeks (Tucker-Lewis Index, TLI), Normlaştırılmamış Uyum İndeksi (Non-Normed Fit Index, NNFI), Normlaştırılmış Uyum İndeksi (Normed Fit Index, NFI), Göreli Uyum İndeksi (Relative Fit Index, RFI), Fazlalık Uyum İndeksi (Incremental Fit Index, IFI) 0.90'nın üzerinde olması kabul edilebilir uyumu, 0,95-1,00 aralığında olması ise mükemmel uyumu göstermektedir. Tahmin hatalarının ortalamasının karekökü (Root Mean Square Error of Approximation, RMSEA) 0,01-0,05 ise mükemmel uyumu, 0,10'a kadar kabul edilebilir model veri uyumunu göstermektedir(31,32). ...
... Confirmatory factor analysis (CFA) has become a key methodology for measuring managerial skills due to its ability to validate theoretical models with empirical data [31][32][33]. Unlike exploratory factor analysis (EFA), which identifies underlying structures without prior hypotheses, CFA allows for confirming the factorial structure of previously defined managerial competencies, ensuring that the indicators used accurately represent the constructs being measured [34][35][36]. ...
... Moreover, by utilizing structural equation modeling, CFA allows for examining complex relationships between latent variables, offering a more detailed view of the impact of managerial skills on sustainable organizational development [38,39,45]. Compared to other techniques, CFA ensures greater statistical robustness and methodological rigor, making it an essential tool for research in management and business development [33,35,36]. ...
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This systematic review explores the most validated methodologies for measuring managerial skills that contribute to sustainable organizational development, with a focus on confirmatory factor analysis (CFA). Using PRISMA guidelines and the PICOS framework, a systematic search in the Web of Science (6810 articles) and Scopus (11,267 articles) identified 27 relevant studies. Our findings emphasize the significance of valid, reliable measurement scales for key managerial competencies, such as leadership, decision-making, communication, and teamwork, which enhance employability and foster sustainable management aligned with the Sustainable Development Goals (SDGs). CFA emerges as a robust technique for ensuring methodological rigor in competency assessment, confirming theoretical models with empirical data. This study identifies gaps in current measurement frameworks, advocating for expanding models to incorporate digital transformation, sustainability leadership, and crisis management skills. Additionally, it underscores the importance of developing context-specific instruments that reflect sectoral and cultural variations. This review contributes to management education and workforce development by providing a validated framework for assessing managerial skills, supporting organizations in aligning leadership training with sustainability-driven business goals. Our findings offer practical implications for designing competency-based curricula and corporate training programs to enhance organizational resilience in an evolving global landscape.
... The proposed mediation model followed the two-step procedure of conducting structural equation modeling [28]. In the first step, confirmatory factor analysis was conducted to test whether the measurement model had an acceptable fit. ...
... (p <.001), CFI = 0.96, TLI = 0.95, RMSEA = 0.05. As suggested by Schumacker and Lomax (2004), observed variables were examined to determine whether their path coefficients from the latent variables were below 0.5 and if latent variables were well measured by their observed variables, and all the factor loadings were above 0.5. ...
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Background The research aims to explore the common nature of ‘kkondae’—a Korean term denoting stubbornness—and its relevance across cultures, particularly examining the relationship between anxiety, kkondae tendencies, and resulting loneliness through difficulties in listening and acceptance in social interactions. Methods A sample of 454 individuals from the U.S. was surveyed online to assess the Korean-developed Kkondae scale’s reliability and validity. Structural Equation Modeling revealed that higher levels of anxiety might lead to increased loneliness, with kkondae traits acting as an intermediary. Results Anxiety was found to affect the tendency towards kkondae behavior, interfering with listening and effective communication, thus exacerbating loneliness. Conclusions Interpersonal communication issues are critical in increasing loneliness. This study adds a new dimension to loneliness research by linking the concept of kkondae with anxiety.
... Overall, the correlation coefficients were positive, providing initial support for the relationships depicted in Figure 1. Examination of skewness and kurtosis for each observed variable revealed that all values fell within the recommended thresholds (skewness ±1.00, kurtosis ±1.50) established by Schumacker and Lomax (2004), thus satisfying the assumption of normality. This confirms their suitability for further analysis. ...
... RMR = .048) (Browne & Cudeck, 1993;Hu & Bentler, 1999;Ingard, 2023a;Kline, 1998;Schumacker & Lomax, 2004), as shown in Figure 1. ...
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This study delves into the factors contributing to the popularity of animated characters among Generation Z viewers, a generation deeply immersed in the digital transformation of entertainment and media. To unravel the allure of animated characters for Generation Z, this research explores their emotional resonance, educational significance, and cultural relevance. The research objectives encompass examining Generation Z viewers' affinity for animated characters, utilizing a quantitative cross-sectional methodology. A sample was selected via convenience sampling, targeting animated movie enthusiasts aged 15 to 26, who participated in an online questionnaire. The study's findings were gathered through a rigorously quality-checked questionnaire, ensuring that the measurement models for both variables, character appearance and character attributes met good quality criteria. This achievement can be attributed to the rigorous development process, which ensured content validity. The results depict a sample predominantly comprised of female university students with a pronounced penchant for animated-style movies. Their preferences lean toward 3D animation and cartoons, particularly favoring animated films segmented into parts or episodes (spin-offs). In evaluating the characters' popularity based on appearance, male characters with endearing features, long hairstyles, superhuman abilities, and contemporary attire garnered the highest favor. Furthermore, when considering character roles, Generation Z respondents displayed a preference for main characters endowed with distinct labels, unique powers, and cheerful, sociable personalities. Characters with significant wealth also piqued their interest.
... The Structural Equation Model serves as an effective instrument for evaluating whether the relationships among the set of variables correspond with the theoretical expectations regarding their causal connections (Stangor, 2004). Schumacker and Lomax (2021) suggested the inclusion of factor analysis in SEM allows the use of multiple indicators for latent variables instead of relying on a single measure, which enhances the reliability and the validity of the constructs. This indicates that Structural Equation Modelling is highly suitable to employ. ...
... Subsequently, we subjected the second phase data (N = 222) to a Confirmatory Factor Analysis (CFA) procedure for estimating various fit indices necessary to validate the structural model. The fit indices values >0.90 for Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) and <0.08 for Root Mean Square Error of Approximation (RMSEA) and Standardized Root Mean Square Residual (SRMR) indicate an acceptable fit criterion (Hooper et al., 2008;Steiger, 2007) whereas the chi-square values less than five indicate a good fit (Schumacker & Lomax, 2004). ...
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Dark Tetrad at Work (DTW) scale is a relatively new instrument used for assessing four dark personality traits, namely; Narcissism, Machiavellianism, Psychopathy and Sadism. In an attempt to psychometrically validate and check its suitability for exploring dark traits among Indian employees, we carried out this two phased study. In the first phase, a total of N = 526 participants working in the government run businesses responded to the scale that was distributed via an online and offline approach. We performed Exploratory Factor Analysis (EFA) on the phase one dataset to test the factor structure and additionally ran correlations and multiple regressions to check the criterion-related validity with organizational constructs such as job burnout and flourishing. We resumed data collection after a small gap and initiated second phase of data collection acquiring a new dataset of N = 222 respondents. We performed Confirmatory Factor Analysis (CFA) on this dataset to examine and validate the factor structure obtained through exploratory factor analysis. The results from the first phase suggested a four-factor solution with best fit and significant factor loadings for all the four factors of the scale, including acceptable convergent and discriminant validity ratios. Our second phase results validated the four-factor solution highlighting good fit indices and suggesting the dark tetrad at work scale can be used to check dark traits in Indian milieu. We highlight limitations of this research and provide future research recommendations advocating translations, cross-cultural, multi-sectoral, exhaustive explorations of the scale to better comprehend the phenomenon.
... The data were analyzed with structural equation modeling (SEM) with a partial least squares (PLS) approach, using SmartPLS 3 software. SEM is a multivariate technique that enables researchers to test complex relationships between variables, variable and construct, and between constructs [91] . The data analysis was conducted in three stages: (1) instrument testing, by assessing reliability and validity; (2) data testing, by evaluating the measurement model (outer model) and ...
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To attract millennials to the agricultural sector, it is necessary to modernize agriculture using social media. Social media plays an important role as a marketing tool for farmers. The utilization of social media platforms can assist farmers in enhancing the effectiveness of their agricultural product marketing efforts, with the objective of increasing their income. This study aimed to determine the effect of social media adoption on the business performance of millennial farmers in Central Java using the technology-organization-environment (TOE) framework. The method used in this study was a quantitative descriptive approach with data collected from 120 millennial farmers located in 10 districts in Central Java. The data analysis method was carried out using SEM-PLS with the SmartPLS 3.0 application. The results of the analysis showed that business performance was in luenced by social media adoption , and millennial farmers' business turnover increased by 25% after using social media. Technological factors and organizational factors had a signi icant effect on social media adoption, while environmental factors were not signi icant. This study provided information on the factors that in luence the business performance of millennial farmers in Central Java Province, which can help farmers in developing strategies to improve business performance and assist the government in developing programs to attract the millennial generation to the agricultural sector.
... The factor loadings were checked at this stage. The goodnessof-fit of the SIDAS was evaluated with the following indicators: comparative fix index (CFI) with an acceptable values greater than 0.9, goodness-of-fit index (GFI) with an acceptable values greater than 0.9, root mean square error of approximation (RMSEA) with an acceptable values less than 0.08, relative fit index (RFI) with an acceptable values greater than 0.9, adjusted goodness of fit index (AGFI) with an acceptable values of more than 0.9, normed fit index (NFI) with an acceptable values of more than 0.9, and incremental fit index (IFI) with an acceptable values of more than 0.9 [25][26][27][28]. ...
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Background The prevalence of Suicidal ideation is increasing in the world. A suitable tool is needed to identify suicide thoughts in the early stage. This study aimed to translation and cultural adaptation of Suicidal Ideation Attributes Scale (SIDAS) among Iranian general people. Methods This study was conducted on 1297 participants (EFA = 364 samples, CFA = 933 samples) in 2024. The psychometric properties of SIDAS including of face validity, content validity, construct validity (confirmatory factor analysis and exploratory factor analysis), Cronbach’s alpha coefficient, intraclass correlation coefficient (ICC), and McDonald’s omega coefficient were evaluated. Results The scores of S-CVI/ Ave and CVR of SIDAS were 1 and 1, respectively. One factor with eigenvalues more than 1 was extracted in EFA section and explained 70.95% variance of SIDAS. In EFA, results showed that the rate of Kaiser Meyer Olkin measure of sampling adequacy was 0.817. In CFA, the one factor was evaluated and confirmed based on the goodness-of-fit indices (for example: CFI = 0.995, RMSEA = 0.061, NFI = 0.994, GFI = 0.992). In reliability section, the McDonald’s omega coefficient, Cronbach’s alpha coefficient, and ICC of SIDAS were 0.931, 0.779, and 0.880, respectively. Conclusion The Persian version of SIDAS was confirmed with One factor and 5 items and this brief scale is appropriate for measure the presence and severity of suicidal thoughts in the general population.
... The analyses were performed using the SPSS and AMOS programs, and fit indices (such as χ²/df, RMSEA, CFI, GFI, and TLI) were evaluated [42]. Table 1 was taken into consideration in the evaluation of the goodness of fit indices [43,44]. ...
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Background This study addresses a gap in the literature by examining how health literacy mediates the relationship between trust in public health authorities and distrust in health systems, particularly in the Turkish context. While previous studies have examined trust and health literacy separately, few have examined trust in health systems regarding health literacy and trust in public health authorities. Therefore, the primary purpose of this study is to determine the mediating role of health literacy in the relationship between trust in public health authorities and distrust in the health system. Methods This research was carried out across Türkiye. In this context, 924 people over 18 years of age participated in the study. As data collection tools, the trust in public health authorities scale, the distrust in health systems scale, and the health literacy scale adapted to Turkish by the researchers were used. Data were collected online via the survey technique. Translation and back-translation methods were used in the scale’s linguistic and cultural adaptation process. While content validity was assessed with expert opinions, structural validity was tested with confirmatory factor analysis (CFA). The reliability of the scale was measured with Cronbach’s alpha coefficient. In addition, the relationship between trust in public health authorities and distrust in health systems was examined using structural equation modeling (SEM), and the mediating role of health literacy in this relationship was analyzed with Bootstrap methods. Results As a result of CFA the adequacy indices of the scale were chi-square/degrees of freedom = 2.940; GFI = 0.946; AGFI = 0.915; CFI = 0.957; NFI = 0.937; and RMSEA = 0.069. The Cronbach’s alpha value of the scale was found to be 0.880. As a result of structural equation modeling, the total effect of Trust in Public Health Authorities on Distrust in Health Systems (β=-0.257; p < 0.001) and the impact on Health Literacy was found to be statistically significant (β=-0.130; p < 0.001). The indirect effects between Trust in Public Health Authorities and Distrust in Health Systems were calculated as -0.064 and − 0.096/-0.037 with a 95% confidence interval, and since these values did not include the 0 range, the indirect effects were found to be statistically significant. Conclusions As a result of the research, it was concluded that health literacy mediates the relationship between trust in public health authorities and distrust in health systems. In this context, public health authorities can pay more attention to sharing information in clear, transparent, and plain language supported by regularly verifiable data to establish trust and communicate effectively with the public.
... In terms of convergent validity, the average variance extracted (AVE) represents the shared variance between a latent variable and its indicators. The AVE indicated that more than half of the variance observed in the items was explained by their underlying constructs, and values of all variables were above the threshold of 0.500, indicating good convergent validity (Schumacker & Lomax, 2004;Henseler et al., 2009). Factor loadings (FLs), the correlation coefficients between each measure item and the latent variable, greater than 0.700 indicate good convergent validity (Fornell & Larcker, 1981), and all measure items in this study met these criteria. ...
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With the rapid development of generative artificial intelligence (AI), AI agents are evolving into “intelligent partners” integrated into various consumer scenarios, posing new challenges to conventional consumer decision-making processes and perceptions. However, the mechanisms through which consumers develop trust and adopt AI agents in common scenarios remain unclear. Therefore, this article develops a framework based on the heuristic–systematic model to explain the behavioral decision-making mechanisms of future consumers. This model is validated through PLS-SEM with data from 632 participants in China. The results show that trust can link individuals’ dual decision paths to further drive user behavior. Additionally, we identify the key drivers of consumer behavior from two dimensions. These findings provide practical guidance for businesses and policymakers to optimize the design and development of AI agents and promote the widespread acceptance and adoption of AI technologies.
... The fit of models was evaluated using three key indices: Comparative Fit Index (CFI), the Root Mean Square Error of Approximation (RMSEA), and the Standardized Root Residual (SRMR). For these indices, acceptable fit values are defined as follows: CFI values should be greater than 0.90 (51,52), RMSEA values should be less than 0.08 and SRMR should be less than 0.1 (53). Factor loadings greater than 0.32 were considered indicative of meaningful loadings (54). ...
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Introduction: Empathy, a complex and multidimensional construct essential for social functioning and mental health, has been extensively studied in both research and clinical settings. The Perth Empathy Scale (PES), a recently developed self-report measure, assesses cognitive and affective empathy across both positive and negative emotions and is based on the self-other model of empathy. This study aimed to evaluate the psychometric properties of the Persian version of the PES in large Iranian sample. Methods: A total of 868 Iranian adults participated in this study. Factorial validity was examined through Confirmatory Factor Analysis (CFA).Internal consistency and concurrent validity were assessed by examining correlations with established empathy measures, including the Interpersonal Reactivity Index (IRI) and the Questionnaire of Cognitive and Affective Empathy (QCAE), as well as the Perth Alexithymia Questionnaire (PAQ) and the Social Phobia Inventory (SPIN). Measurement invariance was also tested between Iranian and Australian samples. Results: The findings supported a three-factor model comprising cognitive empathy, negative affective empathy, and positive affective empathy. The Persian PES demonstrated structural validity, internal consistency, and concurrent validity, suggesting it is a reliable measure for empathy assessment across cultural contexts. Discussion: This study provides empirical support for the validity of the Persian PES and contributes to the expanding body of research on empathy assessment. The results suggest that the PES can be effectively used in Persian speaking populations.
... The CFA indicated that the chi-squared value was χ 2 (142) = 615.09, with a chi-squared/df ratio of χ 2 /df = 2.00, which is within the acceptable range (typically below 3.00), suggesting a reasonable model fit (Schumacker & Lomax, 2016). Additionally, the Standardized Root Mean Square Residual (SRMR) was 0.076, indicating an acceptable fit, as values below 0.08 indicate a good fit (Byrne, 2013). ...
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The rapid integration of computational thinking (CT) into STEM education highlights its importance as a critical skill for problem-solving in the digital age, equipping students with the cognitive tools needed to address complex challenges systematically. This study evaluates CT skills among Engineering and Computer Science students using a multi-method approach by combining quantitative methods (CTT scores and CTS responses) with qualitative methods (thematic analysis of open-ended questions), integrating objective assessments, self-perception scales, and qualitative insights. The Computational Thinking Test (CTT) measures proficiency in core CT sub-competencies, abstraction, decomposition, algorithmic thinking, and pattern recognition through objective tests. The Computational Thinking Scale (CTS) captures students’ perceived CT skills. At the same time, open-ended questions elicit perspectives on the practical applications of CT in academic and professional contexts. Data from 196 students across two Mexican universities were analyzed through quantitative and thematic methods. The results show that students excel in pattern recognition and abstraction but face decomposition and algorithmic thinking challenges. Cross-sectional analyses were conducted between CTT, CTS and the open-ended part to compare CT skills across different demographic groups (e.g., age, gender, academic disciplines), showing clear differences based on age, gender, and academic disciplines, with Computer Science students performing better than engineering students. These findings highlight the importance of CT in preparing students for modern challenges and provide a foundation for improving teaching methods and integrating these skills into university programs.
... We also analyzed chi-square for each model; however, due to the potential for chi-square to inappropriately reject models with large sample sizes, chi-square was not considered when determining model fitness (Weston & Gore, 2006). Additionally, consistent with model respecification processes in SEM, in cases of unacceptable model fitness, we examined modification indices to determine additional parameter constraints to correct model fitness to the data (Schumacker & Lomax, 2010). ...
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The primary focus on the overall higher risk for poor psychosocial and health outcomes has overshadowed inquiries into general psychological processes that might support the psychological well-being of transgender and nonbinary individuals (TNB). Using self-determination theory to assess basic psychological needs (BPN) satisfaction and recent findings about the importance of authenticity to TNB people, we tested the hypothesis that general authenticity would explain positive associations between perceptions of BPN satisfaction and eudaimonic well-being (EWB). We recruited a TNB sample of 489 adults ages 18–61 (M = 26.32, SD = 6.72) who completed a Qualtrics survey hosted on the Prolific Academic platform in 2022. The results of structural equation modeling supported the hypothesized model; people who reported higher levels of BPN satisfaction also reported significantly higher EWB. Higher levels of authenticity partially, but not completely, explained this association. Self-determination theory may be a useful theoretical framework for further understanding barriers and facilitators of TNB adults’ EWB. In the social context of stigma and discrimination, being more authentic helps facilitate one’s BPN satisfaction and thereby supports EWB. These findings have implications for future testing of general psychological processes in the TNB population and interventions to facilitate basic needs satisfaction.
... Fornell and Larcker (1981), proving that the indicators in each factor measure the same concept. The GFI = 0.912 and AGFI = 0.908 indices both exceeded the threshold of 0.9, indicating good agreement between the theoretical model and the actual data, corresponding to the requirements of Schumacker and Lomax (2010). ...
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Background: Vietnam’s educational reform emphasizes competency-based learning to enhance problem-solving skills. Kolb’s Experiential Learning Model (ELM) provides a structured approach to integrating hands-on activities in STEM education, but its effectiveness in secondary education remains underexplored. Purpose: This study examines the applicability of Kolb’s extreme learning machine (ELM) in STEM education and evaluates its impact on ninth-grade students’ problem-solving skills through experiential learning. This study investigates whether hands-on activities improve students’ ability to analyze problems, propose solutions, and apply scientific concepts.Method: A quasi-experimental mixed-methods design was used with 334 ninth-grade students from two secondary schools. The experimental group engaged in a STEM activity constructing a "Revolving Lantern" to explore energy transformation. Data were collected through pre- and post-tests, teacher observations and interviews. Pearson’s correlation and confirmatory factor analysis (CFA) were conducted to assess skill development.Results: The experimental group showed significant improvement in design skills by 150%, problem analysis by 33.33%, and implementation by 33.33%. Pearson’s correlation analysis indicated a moderate relationship between experiential learning stages and problem-solving abilities, with Concrete Experience having the strongest effect. The CFA confirmed the reliability of the assessment framework.Conclusions: Kolb’s ELM enhanced problem-solving skills in STEM education by connecting theory with practice. These findings support its integration into secondary education to foster critical thinking skills and creativity. Future research should explore the long-term impacts and broader applicability of this method.
... In this analysis, the RMSEA was less than 0.05, and the pclose test was not significant (p > 0.05), indicating a close model fit. The Comparative Fit Index (CFI) and the (Schumacker & Lomax, 2004) and values above 0.90 being deemed acceptable (Pituch & Stevens, 2016). In this situation, the CFI measured 0.925 and the TLI was 0.946, both above the 0.90 threshold, which indicates an acceptable fit. ...
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Embodied carbon refers to the greenhouse gas emission associated with the lifecycle of buildings. Embodied carbon policies are critical for addressing the environmental impact of construction materials and advancing climate goals. Despite their importance, the adoption of embodied carbon policies has been limited globally, influenced by economic, environmental, institutional, and trade factors. This study employs structural equation modeling to analyze 37 countries, testing ten hypotheses across four categorical factors. The base model reveals the significant influence of environmental vulnerability and institutional frameworks on policy adoption, while robustness models confirm the critical role of trade dependencies and economic competitiveness in shaping national embodied carbon strategies. Findings underscore that countries with high climate vulnerability and strong institutional support are more likely to adopt embodied carbon policies. Conversely, trade-reliant nations face challenges balancing competitiveness and sustainability. Policy implications suggest the need for international collaboration to align trade policies with carbon reduction goals, targeted support for vulnerable nations, and the integration of embodied carbon considerations into existing climate frameworks. These results offer a roadmap for policymakers to design more effective and equitable embodied carbon policies, fostering global progress toward sustainable construction and decarbonization.
... Minimum sample size was determined based on recommendations to use a minimum of 10 observations per scale item for Confirmatory Factor Analysis (Jackson, 2003;Kline, 2016;Kyriazos, 2018;Schumacker & Lomax, 2016), and was further informed by Comrey and Lee's (1992) classifications of absolute sample size (100 as poor, 200 as fair, 300 as good, 500 as very good, and 1000 as excellent). The longest scales in the present study consist of 20 items (SOCS-S and SOCS-O), and thus a minimum of 200 participants is required. ...
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Objectives There are ongoing debates regarding how compassion is operationalized and measured. The Compassionate Engagement and Action Scales (CEAS) and the Sussex-Oxford Compassion Scales (SOCS) are based on distinct theoretical models with promising empirical support. This study translated the CEAS and SOCS from English to German and validated their psychometric properties in a German-speaking community sample. Method The CEAS and SOCS were translated in a five-stage process including consultation with authors of the original English scales. Participants were recruited online (n = 560) and completed the translated measures as well as questionnaires assessing self-compassion, uncompassionate self-responding, empathic concern, mindfulness, attachment insecurity, depression/anxiety, perceived stress, and mental well-being. Confirmatory Factor Analysis (CFA) was used to assess structural validity, as well as multi-group CFA to assess measurement invariance, and Spearman correlations to assess convergent validity. Results Factor analysis results support the models proposed by scale authors for the CEAS-SC, CEAS-FROM, and SOCS-S. Alternative models are proposed for measures assessing compassion for others (CEAS-TO and SOCS-O). Measurement invariance is supported across age, gender, and education level. Internal consistency and convergent validity results support the use of total and subscale scores for all translated measures. Conclusions The proposed German versions of the CEAS and SOCS provide valid measures for use with German-speaking populations.
... The SEM is a multivariate data analysis method that makes possible the simultaneous modelling and estimation of complex relationships among variables [75]. SEM is used for a better understanding of the multiple observed variables (dependent and independent) in the area of CI research, as the use of a small number of variables for complex phenomena can be limited [76]. The SEM takes measurement error into account while analyzing data and can statistically test theoretical and measurement assumptions against empirical data [77]. ...
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Construction, like any other economic activity, can contribute to national income by creating employment opportunities, and raising gross domestic product (GDP). Several researchers have studied the challenges of various aspects of the construction industry (CI), ranging from sustainability, the industrial revolution, small and medium enterprise, building information modelling, and intelligent construction, but this research examines the state of the CI in conflict-affected regions by evaluating the challenging factors impacting this sector of the economy. A total of 150 industry experts participated in this survey across three regions (Africa, Eastern Europe, and the Middle East). In total, 35 challenging factors were identified and classified using exploratory factor analysis (EFA). Using version 4 of Smart Partial Least Squares (PLS), structural equation modelling (SEM) was used to build the model, which produced seven constructs: economic, environment and education, government, industrial, sustainability, technology, training and support. 31 challenging factors were outlined under these constructs, with economic challenges such as high inflation, high-interest rates, and foreign direct investment (FDI) being the most critical of those observed. This study will be of great importance to the governments of nations in the formulation of policies for the CI. At the same time, stakeholders in the CI will collaborate in the advancement of the sector in the affected region.
... Model χ 2 indices represent overall fit of the model to the data, with nonsignificant results indicating good model fit, and significant results indicating potential problems with model fit. However, the χ 2 statistic is sensitive to sample size, with a higher probability of significance with larger sample sizes (Schumacker & Lomax, 2004). Therefore, we also used alternate diagnostic goodness-of-fit and misfit indices that are less sensitive to sample size. ...
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In a contemporary context where technologies are often (a) crucial venues for adolescent development, sociality, and civic engagement and (b) designed with features that encourage continued use, we ask: How can we assess positive technology use among contemporary adolescents? Using rigorous psychometric methods, we developed a self-report Tech With Care Index among adolescents (ages 13–17) and validated score interpretations. Participants completed two waves of an online survey with the Tech With Care Index, mindfulness measures, intrapersonal and interpersonal measures, and media and technology use measures. After exploratory and confirmatory factor analyses, the final scale included 17 items with four factors: two self-defeating uses (mindless, unhealthy) and two other-benefitting uses (empathic, civic). Subscale scores had reasonable internal reliability, were related to existing mindfulness measures, correlated in predictable ways with other outcomes (e.g., mental health, self-control, empathy, and prosocial behavior), and had high test–retest reliability. The Tech With Care Index addresses the psychological and physical aspects of one’s digital engagement (caring for self) and attention beyond oneself to social and civic considerations (caring for others). It contributes to a growing literature on positive technology, providing a tool for researchers and practitioners to assess and attempt to build thoughtful and prosocial technology use.
... The structural equation model (SEM) presented in Figure 3 evaluated the relationships among four latent constructs-social, economic, environmental, and technical factors-as measured by their respective observed variables. The model demonstrated an acceptable fit to the data, as indicated by several fit indices: chi-square/df = 1.512 (below the threshold of 3, suggesting a good fit [68]), CFI = 0.918 (exceeding the recommended minimum of 0.90 for model acceptability [69]), and RMSEA = 0.067, with PCLOSE = 0.066 (within the acceptable range of ≤0.08, indicating a reasonable approximation of the population [70]). Although the goodness-of-fit index (GFI = 0.841) is slightly below the preferred threshold of 0.90, it remains acceptable in exploratory research contexts or the sample size is small [71]. ...
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The construction industry is increasingly prioritizing sustainability, with the selection of sustainable construction materials (SCMs) playing a crucial role in achieving environmental and regulatory objectives. However, New Zealand’s construction codes and sustainability standards lack cohesive, region-specific guidance, posing challenges for industry professionals in selecting appropriate materials. This study aims to identify the key factors influencing SCM selection within the New Zealand construction sector. An online questionnaire was distributed to 115 industry professionals, and data were analyzed using a structural equation modeling (SEM) with confirmatory factor analysis (CFA) to examine the relationships among social, economic, environmental, and technical factors. The finding was that technical factors are vital in achieving sustainable construction. Additionally, the social, economic, environmental, and technical factors were strongly correlated, affecting the selection of SCMs. Based on this research, construction consultants should advise customers on materials and the long-term economic benefits of investing in sustainable materials, which will cut operating expenses and environmental effects.
... Correlational design is a research method that aims to evaluate and describe the extent of the relation between two or more variables or scores without intervention (Curtis et al., 2016;Creswell, 2013Creswell, /2019. Path analysis (Schumacker & Lomax, 2004), an advanced statistical method, was used to answer this question. Path analysis is a statistical analysis method that is based on examining the relations between the variables in the research in detail by modeling and testing the accuracy of the model (Christensen et al., 2015), used to determine the existence of causal relations of at least three variables and more effective than other analysis methods in terms of causality tests (Fraenkel et al., 1993). ...
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Social skills acquired during the early childhood period contribute tochildren’s development of healthy self-esteem and effectiverelationships throughout their lives, while parent-child relationshipsplay a critical role in the development of social skills and psychologicalresilience. In this context, this study aimed to examine the mediatingrole of psychological resilience in father–child relationships and socialskills in early childhood. The study was conducted with 375 fathers ofchildren aged 0–8 in Turkey. The results indicate that positive father–child interactions significantly enhance children’s social skills andpsychological resilience, which in turn further improves socialcompetence. Psychological resilience was found to partially mediatethese relations, highlighting its importance as a protective factor inchildren’s socio-emotional development. These findings underline thecritical role of fathers in early childhood development and suggeststrengthening early childhood education programs to support father–child relationships, developing training based on family communicationand psychological resilience.
... 3) are produced in order to verify how well the hypothesized model reproduces the observed covariance matrix (Nassivera, Sillani, 2017;Sillani, Nassivera, 2015;Cheah et al., 2018). Specifically, the selected indexes are: the goodness of fit index (GFI) and adjusted goodness of fit index (AGFI), both proposed by Schumacker and Lomax (2004); the incremental fit indexes or normed fit index (NFI), proposed by Bentler and Bonnett (1980); the non-normed fit index (NNFI), as proposed by Bollen and Liang (1988); the comparative fit index (CFI), proposed by Bentler (1990); and the root mean square error of approximation (RMSEA), proposed by Browne and Cudeck (1992). The results indicated a good fit between the model and observed data and allowed for the analysis of the assumptions of the hypotheses. ...
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... The chi-square test (χ² = 399.820, p = 0.083) indicates no significant discrepancy between the observed and model-implied covariance matrices, suggesting an acceptable model fit (Schumacker & Lomax, 2015). The χ²/df ratio (1.104) falls well below the threshold of 3, further supporting model adequacy (Kline, 2023). ...
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... As can be seen in Tables 5 and 6, as well as in Figure 1, all of the formulated hypotheses were conrmed. The t of the model was assessed with several indicators, and the results were compared with the thresholds recommended by Schumacker and Lomax (2004) and Hu and Bentler (1999). This supports the notion that attendance in extracurricular activities during school years can enhance the chances for participation in learning in adulthood regardless of one's family background. ...
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... As illustrated in Fig. 2, all the model-fit measures (CFI, NFI, TLI, AGFI, GFI, RMSEA, Chisq/df ) were within acceptable threshold values recommended by previous studies [66,68,69], indicating that the proposed model demonstrated a satisfactory fit with the observed data, and structural model analysis can be performed [70]. ...
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FR Cet article teste le cadre conceptuel de l'OCDE sur la confiance dans les institutions. Nous utilisons l'enquête sur la confiance dans les institutions menée par l'OCDE dans 18 pays en 2021. À l'aide d'un modèle d'équation structurelle, nous estimons un modèle factoriel confirmatoire pour trois dimensions sous-jacentes : la confiance dans la politique, la confiance dans les institutions et la qualité de la gouvernance. Les scores de ces facteurs sont ensuite utilisés dans une analyse de régression afin d'explorer systématiquement les déterminants socio-économiques tels que l'âge, le sexe et le niveau d'éducation, et de comparer les résultats à ceux du rapport de l'OCDE de 2022. Notre étude corrobore presque tous les effets sociodémographiques sur la confiance décrits dans le rapport. En outre, notre étude met en évidence le rôle important de la qualité de la gouvernance en tant que prédicteur robuste des niveaux de confiance globaux. Enfin, pour vérifier la robustesse des régressions par les MCO, nous utilisons également une approche de régression distributionnelle à l'aide de régressions non paramétriques (fonctions d'influence recentrées). Nos résultats révèlent des schémas clairs : aux quantiles inférieurs de confiance, le sexe, le niveau d'éducation et le revenu présentent des relations positives et significatives. À l'inverse, aux quantiles supérieurs, et en particulier au quantile 0,90, leur impact passe à une association négative. Ces résultats soulignent l'importance de vérifier les associations non linéaires, qui peuvent produire des résultats sensiblement différents par rapport aux cadres traditionnels des MCO. EN This paper tests the OECD conceptual framework of trust in institutions. We use the survey on trust in institutions administered by the OECD in 18 countries in 2021. Employing a structural equation model, we estimate a confirmatory factor model for three underlying dimensions: trust in politics, trust in institutions, and quality of governance. These factors' scores are then used in a regression analysis in order to systematically explore socioeconomic determinants such as age, gender, and education level, and compare the findings to those of the 2022 OECD report. Our study corroborates almost all the sociodemographic effects on trust described in the report. Furthermore, our study highlights the important role of quality of governance as a robust predictor of overall trust levels. Finally, to check the robustness of the OLS regressions, we also employ a distributional regression approach using non-parametric regressions (re-centered influence functions). Our findings reveal clear patterns: at lower quantiles of trust, gender, education level, and income exhibit positive and significant relationships. Conversely, at higher quantiles, and particularly the 0.90 quantile, their impact shifts to a negative association. These results underscore the importance of checking non-linear associations, which may yield markedly different outcomes compared to traditional OLS frameworks. Abstract This paper tests the OECD conceptual framework of trust in institutions. We use the survey on trust in institutions administered by the OECD in 18 countries in 2021. Employing a structural equation model, we estimate a confirmatory factor model for three underlying dimensions: trust in politics, trust in institutions, and quality of governance. These factors' scores are then used in a regression analysis in order to systematically explore socioeconomic determinants such as age, gender, and education level, and compare the findings to those of the 2022 OECD report. Our study corroborates almost all the sociodemographic effects on trust described in the report. Furthermore, our study highlights the important role of quality of governance as a robust predictor of overall trust levels. Finally, to check the robustness of the OLS regressions, we also employ a distributional regression approach using non-parametric regressions (re-centered influence functions). Our findings reveal clear patterns: at lower quantiles of trust, gender, education level, and income exhibit positive and significant relationships. Conversely, at higher quantiles, and particularly the 0.90 quantile, their impact shifts to a negative association. These results underscore the importance of checking non-linear associations, which may yield markedly different outcomes compared to traditional OLS frameworks.
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