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Advances in Factor Analysis and Structural Models
... After determining the factorial solution, we selected and smaller subsample randomly (50%) to apply the Exploratory Factor Analysis (Ferrando, & Lorenzo-Seva, 2014) and identify the factorial solution; after that we have proceeded with a confirmatory factor analysis (CFA), accompanied by the goodness of fit indices. Confirmation of the adequacy of the model have been stablished from the following indices: the chi-square statistic X 2 (Jöreskog & Sörbom, 1979;Saris & Stronkhorst, 1984); the goodness of fit index (GFI), considered to be acceptable when its value is over .90 (Bentler, 1990); the root mean square residual (RMSR) and the error of the root mean square approximation (RMSEA), both considered acceptable when taking values under .08 ...
... (Bentler, 1990); the root mean square residual (RMSR) and the error of the root mean square approximation (RMSEA), both considered acceptable when taking values under .08 (Jöreskog & Sörbom, 1979;Steiger & Lind, 1980); and the incremental fit indices, namely the comparative fit index (CFI), the normed fit index (NFI), also called delta 1 and the incremental fit index (IFI), ranging these three indices from 0 to 1 and being considered acceptable over .90 (Bentler, 1990). ...
In this work we describe an instrument based on the use of a factor analysis technique in order to measure the quality of education within a Postgraduate degree offered by a public Spanish university. We showed that the instrument has satisfactory psychometric properties (relia-bility and validity). Regarding the factorial solution, three main dimensions have been determined, namely: importance given to the subject; educational resources and knowledge of the subject (previous and posterior). It is important to remark that these three dimensions were consistently detected in all the factorial analyses performed (total sample and separate academic years). These three dimensions should be considered as fundamental when designing an instrument to evaluate educational quality. These findings may be taken as a basis for the design of future strategies for the evaluation of educational quality on other type of degrees within the higher education area .
... There are a number of psychometric reasons for needing to validate scores of an instrument used with different age groups. An instrument is not transferable to different contexts unless its scores have both temporal generalizability and ecological generalizability (Bracht & Glass, 1968; Emmerich, 1964 Emmerich, , 1968 Jöreskog & Sörbom, 1979; Kagan, 1971; Messick, 1989; Tucker, 1966). Temporal generalizability refers to the need for age and developmental levels to be taken into consideration when constructing the validity of an instrument and addresses whether or not the participant's age and development levels are appropriate for the instrument. ...
... Temporal generalizability refers to the need for age and developmental levels to be taken into consideration when constructing the validity of an instrument and addresses whether or not the participant's age and development levels are appropriate for the instrument. (Emmerich, 1964Emmerich, , 1968 Jöreskog & Sörbom, 1979; Kagan, 1971; Messick, 1989; Tucker, 1966). Ecological generalizability refers to creating an instrument that can span across age groups, gender, socio-economic groups, and geographical locations (i.e., urban, rural, or suburban). ...
... In this study, the LGCM was fit to data using Mplus (version 7.1) with a robust maximum likelihood estimator. Four model fit indexes were applied to evaluate the adequacy of model fit [24]: (a) chi-square statistics [20], (b) the Bentler Comparative Fit Index (i.e., CFI ≥ 0.9 [3,5];, and (c) root mean square error of approximation (i.e., RMSEA ≤0.05) with 90% confidence interval [45]. Significant chi-square difference (∆χ 2 ) tests, which were used to determine significant differences between constrained and unconstrained models, indicated determinants that showed significantly different influences on men's and women's disability trends [36]. ...
Abstract Background Researchers have emphasized the importance of examining how different factors affect men’s and women’s functional status over time. To date, the literature is unclear about whether sex affects the rate of change in disability in middle to older age. Researchers have further emphasized the importance of examining how different factors affect men’s and women’s functional status over time. We examined (a) sex differences in disability trends and (b) the determinants of the rate of change in disability for men and women 50 years and older. Methods This study utilized the Taiwan Longitudinal Study on Aging Survey, a nationally representative database (four waves of survey data 1996–2007, N = 3429). We modeled and compared the differences in disability trends and the influences of determinants on trends among men and women using multiple-indicator and multiple-group latent growth curves modeling (LGCM). Equality constraints were imposed on 10 determinants across groups. Results Once disability began, women progressed toward greater disability 18% faster than men. Greater age added about 1.2 times the burden to the rate of change in disability for women than men (p
... This analysis was undertaken to confirm the fit of the original factorial structure of the instruments with the Spanish families. To carry out the CFA, the suitability of the model was confirmed by the use of the following absolute-fit indices: chi-square (Jöreskog & Sörbom, 1979;Saris & Stronkhorst, 1984), the comparative-fit index (CFI), and the normed-fit index (NFI), also called delta 1. In all cases, the range of values is between 0 and 1 and the reference value is 0.90 (Bentler, 1990;Bollen, 1989). ...
Family quality of life (FQoL) is considered one of the aims of early intervention (EI) services and a good indicator of service quality. Families were recruited from EI centers in 12 of 17 communities (states) in Spain. This study describes the FQoL of 250 Spanish families with children aged 0 to 6 years in EI services during a family-centered implementation process. We used an EI-specific FQoL scale that includes families’ perception of their child’s functioning as one factor. We also describe the relationships among individual, family, and service variables as well as FQoL. Type of disability, socioeconomic status, and family-centered practices impacted Child Functioning, Overall Life Situation, and Access to Information and Services factors, respectively. Fewer number of professionals involved was related with greater perception of child’s functionality. Family-centeredness, type of family, and type of disability were the most influencing variables for the Total score. Implications for practice are discussed.
... The data were analysed using Structural Equation Modelling (SEM), which combines path-analysis, simultaneousequation models and factor analysis [33, 34]. It enables estimating associations of latent variables (unobserved variables, measured with multiple items) and estimating multiple regression equations, including more than one dependent variable in one model. ...
Background
As the implementation of Electronic Medical Records (EMRs) in hospitals may be challenged by different responses of different user groups, this paper examines the differences between doctors and nurses in their response to the implementation and use of EMRs in their hospital and how this affects the perceived quality of the data in EMRs. Methods
Questionnaire data of 402 doctors and 512 nurses who had experience with the implementation and the use of EMRs in hospitals was analysed with Multi group Structural equation modelling (SEM). The models included measures of organisational factors, results of the implementation (ease of use and alignment of EMR with daily routine), perceived added value, timeliness of use and perceived quality of patient data. ResultsDoctors and nurses differ in their response to the organisational factors (support of IT, HR and administrative departments) considering the success of the implementation. Nurses respond to culture while doctors do not. Doctors and nurses agree that an EMR that is easier to work with and better aligned with their work has more added value, but for the doctors this is more pronounced. The doctors and nurses perceive that the quality of the patient data is better when EMRs are easier to use and better aligned with their daily routine. Conclusions
The result of the implementation, in terms of ease of use and alignment with work, seems to affect the perceived quality of patient data more strongly than timeliness of entering patient data. Doctors and nurses value bottom-up communication and support of the IT department for the result of the implementation, and nurses respond to an open and innovative organisational culture.
... Heuristic search techniques leverage information-theoretic algorithms from the field of artificial intelligence (e.g., mathematically-based approaches based on lagrangian heuristic/incomplete branch-andbound algorithms). Application of SEM involves measuring the discrepancy between a parameterized causal structure of hypothesized relationships (e.g., between observed or latent variables or a combination of both) and estimated parameters from data as measured through a series of fit indices [10,11]. SEM employing Bayesian probability and statistics [12,13] has recently emerged and provides increased precision and flexibility in modeling scenarios with high dimensional data structures, small sample size and non-normally distributed variables. ...
Advances in the sophistication of imaging techniques necessitate the development of techniques to model the neural and cognitive phenomena they represent. Using electrocorticographic (ECoG) data, we propose a data-driven approach using ordinary differential equations and Bayesian differential structural equation modeling (BdSEM) to model effective connectivity related to sensorimotor integration. First, we tested the region-based covariance structure across subjects by each experimental condition to evaluate the tenability of pooling subject data to perform group level versus single-subject analyses. Second, we applied a differential equation approach to model dynamic change originating from regional neuronal states across the data acquisition period. Finally, we employed an information-theoretic search strategy to identify the optimal connectivity model within each experimental condition for a single subject. Results of subject-specific (intra-individual) relationship maps include effective, contemporaneous and delayed effective connections of across different brain regions.
... The data are analysed using SEM. SEM, also known as latent variable analysis, combines path-analysis, simultaneous equation models and factor analysis [44, 45]. It enables to estimate associations of latent variables (unobserved variables, measured with multiple items), to estimate multiple regression equations, including more than one dependent variable in one model, and to study whether hypothesized paths are corroborated by the underlying data. ...
Background:
Escalation of commitment is the tendency that (innovation) projects continue, even if it is clear that they will not be successful and/or become extremely costly. Escalation prevention potential (EPP), the capability of an organization to stop or steer implementation processes that do not meet their expectations, may prevent an organization of losing time and money on unsuccessful projects. EPP consists of a set of checks and balances incorporated in managerial practices that safeguard management against irrational (but very human) decisions and may limit the escalation of implementation projects. We study whether successful implementation of electronic medical records (EMRs) relates to EPP and investigate the organizational factors accounting for this relationship.
Methods:
Structural equation modelling (SEM), using questionnaire data of 427 doctors and 631 nurses who had experience with implementation and use of EMRs in hospitals, was applied to study whether formal governance and organizational culture mediate the relationship between EPP and the perceived added value of EMRs.
Results:
Doctors and nurses in hospitals with more EPP report more successful implementation of EMR (in terms of perceived added value of the EMR). Formal governance mediates the relation between EPP and implementation success. We found no evidence that open or innovative culture explains the relationship between EPP and implementation success.
Conclusions:
There is a positive relationship between the level of EPP and perceived added value of EMRs. This relationship is explained by formal governance mechanisms of organizations. This means that management has a set of tangible tools to positively affect the success of innovation processes. However, it also means that management needs to be able to critically reflect on its (previous) actions and decisions and is willing to change plans if elements of EPP signal that the implementation process is hampered.
To investigate the influence of the home environment, defined as family socioeconomic status (SES) (parent education level, household income), student resource-mediated SES (access to nutritional resources and cognitively stimulating experiences), reading ability, and difficulty with homework on quality of life in children and adolescents residing in urban and suburban areas in Hangzhou City, Zhejiang Province, China. This study included 3200 Grade 3–6 students from 8 elementary schools in Hangzhou City. Assessments included questionnaires that evaluated student quality of life, family SES, resource-mediated SES (dietary behavior and the home literacy environment), reading ability, and difficulty with homework. The effects of the home environment on student quality of life were analyzed by univariate analysis, multiple linear regression analysis, and structural equation modeling. Overall, 80.6% of students had a medium or better quality of life. Young age (Grade 3 or 4), female sex, household income of 10000–15000 RMB, high breakfast consumption, daily intake of fruit, a balanced diet, and good reading habits were positively correlated with student quality of life ( P < 0.05), while overuse of electronic devices was negatively correlated with quality of life ( P < 0.05). Dietary behaviors, home literacy environment, and student reading ability and difficulty with homework directly affected quality of life. Family SES indirectly affected student quality of life. Children and adolescents in China should have access to good nutrition and cognitively stimulating experiences to enhance their well-being and provide them with social and academic advantages.
The purpose of this article is to analyse the importance of emotions in a wine tasting experience for inexperienced participants. It is necessary to reduce elitism because customers who are not knowledgeable and inexperienced in wines can also do a wine tasting. They are also important consumers. The empirical study includes a questionnaire (n = 146) applied to inexperienced wine tasting participants. A conceptual model was built, and the results show that the composite of emotions: Comfort and Enthusiasm of participants can have a positive effect on their Satisfaction and consequent Word of Mouth. This study provides a relevant information on how wine companies can effectively promote wine tasting to inexperienced participants, and offer important implications for wine companies, especially for those offering wine tasting experiences to their visitors/customers. These types of participants are potential consumers and have significant importance for the market share.
Background
Although obsessive compulsive disorder (OCD) is effectively treated by cognitive behavior therapy (CBT), less is known about mechanisms underlying treatment response. Anxiety sensitivity (AS) may impact symptom change (velocity) and the rate of change in velocity (acceleration) during CBT for OCD. Latent Difference Score (LDS) analysis was used to show path-analytic dynamic modelling of OCD symptom velocity and acceleration during CBT, as a function of baseline AS.Method
Eighty-four participants with a principal diagnosis of OCD completed 12 weeks of CBT group therapy, and measures assessing AS at pre-treatment, and obsession and compulsion severity at pre-treatment, sessions 4, 8, and end of treatment.ResultsLDS velocity models demonstrated that higher levels of baseline AS were associated with subsequent elevations in obsessions throughout treatment, and obsession scores were temporally associated with subsequent changes in compulsion scores. An LDS acceleration model demonstrated that higher levels of baseline AS scores were associated with rapid increases in the severity of obsessions, whereas lower AS scores were associated with rapid decreases in the severity of obsessions.DiscussionThese results have implications for theoretical and treatment modelling of obsessions and compulsions, as well as AS, in OCD.Conclusion
Higher levels of baseline AS negatively impact response to CBT for OCD.
Chan et al. (2012) have proposed an innovative Entrepreneurship, Professionalism and Leadership (EPL) framework for understanding career growth and development in the 21st century. To date, there are no studies examining how EPL aspiration changes over time. This paper attempts to characterize the variation of EPL motivation across time from 1,748 university students using the Latent Difference Score (LDS) approach. Changes in EPL dimensions were found to be inter-related, and differences in the EPL development between Science, Technology, Engineering, and Mathematics (STEM) and non-STEM students were detected.
Procrastination, mental health problems, and decreased life satisfaction among university students constitute an issue over which there is growing public concern. Yet, there is little research explaining the mechanisms through which academic procrastination may lead to less life satisfaction. The present study aimed to explore the link between procrastination and psychopathology among 2 samples (sample 1, N = 681, and sample 2, N = 183) of Greek University students. We also further tested the assumption that psychological distress would mediate the relationship between procrastination and life satisfaction. Data were analyzed using correlational analyses and structural equation modeling. In the first Study, procrastination was related to psychopathology. In the second study, results revealed that students who had the tendency to procrastinate in general, or their academic obligations, in particular, reported less psychological well-being, more anxiety, more psychological distress, less emotional ties, less general positive affect, more loss of behavioral and emotional control, more depressive symptoms and less life satisfaction. More importantly, the model exhibited a good fit for the data, while the bootstrapped standardized indirect effect of procrastination on life satisfaction was statistically significant supporting the hypothesis that psychological distress partially mediated the relationship between procrastination and life satisfaction. In conclusion, difficulty to meet deadlines within a specific time-frame is related to worse mental health and decreased overall life satisfaction academic procrastination, general procrastination, psychopathology, mental health, life satisfaction.
A common way to form scores from multiple-item scales is to sum responses of all items. Though sum scoring is often contrasted with factor analysis as a competing method, we review how factor analysis and sum scoring both fall under the larger umbrella of latent variable models, with sum scoring being a constrained version of a factor analysis. Despite similarities, reporting of psychometric properties for sum scored or factor analyzed scales are quite different. Further, if researchers use factor analysis to validate a scale but subsequently sum score the scale, this employs a model that differs from validation model. By framing sum scoring within a latent variable framework, our goal is to raise awareness that (a) sum scoring requires rather strict constraints, (b) imposing these constraints requires the same type of justification as any other latent variable model, and (c) sum scoring corresponds to a statistical model and is not a model-free arithmetic calculation. We discuss how unjustified sum scoring can have adverse effects on validity, reliability, and qualitative classification from sum score cut-offs. We also discuss considerations for how to use scale scores in subsequent analyses and how these choices can alter conclusions. The general goal is to encourage researchers to more critically evaluate how they obtain, justify, and use multiple-item scale scores.
Cognitive behavioural therapy (CBT) for Social Anxiety Disorder (SAD) is an effective intervention for SAD, however, many individuals with SAD remain symptomatic at the end of CBT. Therefore, it is important to understand variables that influence patients’ responses to treatment. The present study investigated temporal changes in SAD symptoms as related to fear of negative evaluation (FNE) in a clinical sample of individuals with SAD who completed CBT. Participants with SAD (N = 175) completed self-report measures of SAD symptoms and FNE weekly across 12 weeks of group CBT. We used latent difference score dynamic modelling to explore the relationship between SAD symptom scores and FNE during CBT. Reductions in FNE were associated with subsequent reductions in SAD symptoms for individuals who showed a rapid response to treatment. The coupling of FNE and subsequent reductions in SAD symptoms was not seen in individuals not showing a rapid response. This study provides further support for the phenomenon of rapid response in CBT for SAD and suggests that mechanisms of change may be different for rapid responders as compared to non-rapid responders. The results of the current study may have implications for understanding the mechanisms underlying treatment response during CBT for SAD and for whom particular mechanisms are relevant.
One of the main issues in the field of product aesthetics is the lack of consistency in the instruments and terms being used to assess it. Several scales have been used but with restricted validity and reliability; notwithstanding, the APID (Aesthetic Pleasure In Design) scale developed in English, as part of the UMA (Unified Model of Aesthetics) project, lacks these limitations. Our research, being in a Spanish speaking country, required the scale to be in Spanish to be comprised and applied to domestic respondents. The adaptation of psychometric instruments with conceptual and linguistic challenging constructs, often is difficult, as the items used to assess the construct do not always have a direct translation. Also, it is possible for the adapted version to require different items that were not considered in the original instrument in order to preserve the content’s equivalence according to the target culture. A qualitative-quantitative mixed approach is proposed in order to overcome these issues. The resulting instrument has been statistically tested, proving to be both valid and reliable for the measurement of aesthetic pleasure in design. The final scale consists of five items: bonito, hermoso, agradable, llamativo and me gusta. This paper aims to improve the understanding of how aesthetic pleasure is perceived and therefore expressed by the local respondents gaining insight into how this construct is mentally represented and categorized by the respondents. It also aims to illustrate how psychometric scales based on respondents’ vocabulary have a great potential as usability assessment instruments.
The Intermodal Surface Transportation Efficiency Act (ISTEA) mandates that individual states develop six transportation infrastructure management systems. One of these systems, the safety management system (SMS), focuses on reducing the number of roadway traffic accidents, injuries, and fatalities by considering the safety needs of the driver, vehicle, and roadway. This necessitates cooperation among state, city, and county roadway agencies as well as diverse public and quasi-public agencies. States have made significant advances toward implementing SMSs. The safety community recognizes that it is time to coordinate safety activities and responsibilities. Even if it is not mandated by Congress, as recent actions indicate, a large number of states are expected to implement elements of their SMS work plan. With this implementation comes the need for the evaluation of SMS's effectiveness in increasing traffic safety and ultimately reducing the number and severity of accidents. The challenge in evaluating SMS effectiveness is that many of the activities undertaken will not be directly quantifiable by accident statistics. Discussed here are some of the impediments, concerns, and design issues in an evaluation of SMS effectiveness in increasing traffic safety. Knowledge of these impediments and determination of an appropriate experimental design will enable the prior planning required to perform valid effectiveness evaluations.
Objectives
To determine the mediating effects of depression on health-related quality of life and fatigue in individuals with multiple sclerosis (MS).
Design
A cross-sectional study.
Setting
Tertiary urban hospital.
Participants
One hundred and eight patients (54% women) with MS participated in this study.
Outcome measures
Demographic and clinical data (weight, height, medication and neurological impairment), fatigue (Fatigue Impact Scale), depression (Beck Depression Inventory-II) and health-related quality of life (Short-Form Health Survey 36) were collected.
Results
Fatigue was significantly associated with bodily pain, physical function, mental health and depression. Depression was associated with bodily pain and mental health. The path analysis found direct effects from physical function, bodily pain and depression to fatigue (all, P<0.01). The path model analysis revealed that depression exerted a mediator effect from bodily pain to fatigue (B=−0.04, P<0.01), and from mental health to fatigue (B=−0.16, P<0.01). The amount of fatigue explained by all predictors in the path model was 37%.
Conclusions
This study found that depression mediates the relationship between some health-related quality of life domains and fatigue in people with MS. Future longitudinal studies focusing on proper management of depressive symptoms in individuals with MS will help determine the clinical implications of these findings.
This paper presents a novel framework for maximum likelihood (ML) estimation in skew-t factor analysis (STFA) models in the presence of missing values or nonresponses. As a robust extension of the ordinary factor analysis model, the STFA model assumes a restricted version of the multivariate skew-t distribution for the latent factors and the unobservable errors to accommodate non-normal features such as asymmetry and heavy tails or outliers. An EM-type algorithm is developed to carry out ML estimation and imputation of missing values under a missing at random mechanism. The practical utility of the proposed methodology is illustrated through real and synthetic data examples.
To predict the possible evolutionary response of a plant species to a new environment, it is necessary to separate genetic from environmental sources of phenotypic variation. In a case study of the invader Solidago altissima, the influences of several kinds of parental effects and of direct inheritance and environment on offspring phenotype were separated. Fifteen genotypes were crossed in three 5 × 5 diallels excluding selfs. Clonal replicates of the parental genotypes were grown in two environments such that each diallel could be made with maternal/paternal plants from sand/sand, sand/soil, soil/sand, and soil/soil. In a first experiment (1989) offspring were raised in the experimental garden and in a second experiment (1990) in the glasshouse. Parent plants growing in sand invested less biomass in inflorescences but produced larger seeds than parent plants growing in soil. In the garden experiment, phenotypic variation among offspring was greatly influenced by environmental heterogeneity. Direct genetic variation (within diallels) was found only for leaf characters and total leaf mass. Germination probability and early seedling mass were significantly affected by phenotypic differences among maternal plants because of genotype (genetic maternal effects) and soil environment (general environmental maternal effects). Seeds from maternal plants in sand germinated better and produced bigger seedlings than seeds from maternal plants in soil. They also grew taller with time, probably because competition accentuated the initial differences. Height growth and stem mass at harvest (an integrated account of individual growth history) of offspring varied significantly among crosses within parental combinations (specific environmental maternal effects). In the glasshouse experiment, the influence of environmental heterogeneity and competition could be kept low. Except for early characters, the influence of direct genetic variation was large but again leaf characters (= basic module morphology) seemed to be under stricter genetic control than did size characters. Genetic maternal effects, general environmental maternal effects, and specific environmental maternal effects dominated in early characters. The maternal effects were exerted both via seed mass and directly on characters of young offspring. Persistent effects of the general paternal environment (general environmental paternal effects) were found for leaf length and stem and leaf mass at harvest. They were opposite in direction to the general environmental maternal effects, that is the same genotypes produced "better mothers" in sand but "better fathers" in soil. The general environmental paternal effects must have been due to differences in pollen quality, resulting from pollen selection within the male parent or leading to pre- or postzygotic selection within the female parent. The ranking of crosses according to mean offspring phenotypes was different in the two experiments, suggesting strong interaction of the observed effects with the environment. The correlation structure among characters changed less between experiments than did the pattern of variation of single characters, but under the competitive conditions in the garden plant height seemed to be more directly related to fitness than in the glasshouse. Reduced competition could also explain why maternal effects were less persistent in the glasshouse than in the garden experiment. Evolution via selection of maternal effects would be possible in the study population because these effects are in part due to genetic differences among parents.
This paper presents a new algorithm estimating structural equation models by using the generalized structured component analysis (GSCA) formulation. In GSCA models, the latent variables are composites. The weights are estimated in conjunction with the other model parameters, optimizing a genuine least squares criterion. The new algorithm is designed for three subclasses often used in applications. Linear regressions are alternated for different sets of parameters according to the nonlinear manner in which the parameters are incorporated in the model. The new algorithm is compared with two existing ones by using different examples from the literature, as well as simulations. On the average the proposed algorithm produces better criterion values compared to the other two ones.
Karl G. Joreskog (b. 1935) has enjoyed a long and distinguished career as a behavioral science statistician. He is best known for his creation (along with Dag Sorbom) of the LISREL computer program for data analysis for linear structural equation models (SEM). He has done much more. He has taught generations of social and behavioral scientists how to apply this approach to their own SEM problems, and this has changed the way many of us think about multivariate analysis.
Keywords:
statistical methods in psychology;
testing in psychology;
systems and networks
BackgroundA better understanding of potential relationship between mood disorders, sleep quality, pain, and headache frequency may assist clinicians in determining optimal therapeutic programs. The aim of the current study was to analyze the effects of sleep quality, anxiety, depression on potential relationships between headache intensity, burden of headache, and headache frequency in chronic tension type headache (CTTH). Methods
One hundred and ninety-three individuals with CTTH participated. Headache features were collected with a 4-weeks headache diary. The Hospital Anxiety and Depression Scale was used for assessing anxiety and depression. Headache Disability Inventory evaluated the burden of headache. Pain interference was determined with the bodily pain domain (SF-36 questionnaire). Sleep quality was assessed with Pittsburgh Sleep Quality Index. Path analyses with maximum likelihood estimations were conducted to determine the direct and indirect effects of depression, anxiety, and sleep quality on the frequency of headaches. ResultTwo paths were observed: the first with depression and the second with sleep quality as mediators. Direct effects were noted from sleep quality, emotional burden of disease and pain interference on depression, and from depression to headache frequency. The first path showed indirect effects of depression from emotional burden and from sleep quality to headache frequency (first model R2 = 0.12). Direct effects from the second path were from depression and pain interference on sleep quality and from sleep quality on headache frequency. Sleep quality indirectly mediated the effects of depression, emotional burden and pain interference on headache frequency (second model R2 = 0.18). Conclusions
Depression and sleep quality, but not anxiety, mediated the relationship between headache frequency and the emotional burden of disease and pain interference in CTTH.
Factor analysis is a branch of analysis of variance used to investigate the structure of a data set. Consider a data set x
ij
resulting from the observation of several variables j on several objects i. If the data set arises from a complex multidimensional process about which little is known a priori statistical analysis of the data itself might profitably be used to gain insights into various characteristics of the processes which generated the data set. In particular, statistical techniques can be used to: (1) search for a simpler representation of the underlying processes which generated the data by reducing the dimension of the variable space in which the objects are represented; (2) look for the interactions among the variables by forming linear clusters of variables; and (3) seek characterizations of the clusters of variables which relate them to the underlying processes which generated the data set being analysed. Factor analysis performs all three functions.
Currently, measuring cause and effect relationship for an intangible situation such as customer satisfaction has been gaining momentum. For this, two statistical techniques are used: (i) structural equation modeling-SEM with co-variance matrix, and (ii) partial least squares-PLS, which determine, as multivariate technique, the relationship between observable and latent variables in order to test a series of associations. In this sense, this paper is aimed at presenting each of the techniques (SEM and PLS) from an interpretative perspective, by means of a case study. As a result, one of the differences found between the methods is the estimation procedure, since SEM is oriented towards theory, emphasizing the transition from exploratory analysis to confirmatory, whereas PLS is focused on the causal-predictive analysis in high complexity situations, though with little theoretical information. Both methods pursue different goals and should not be exclusionary but complementary, based on the interests of the researcher and the objectives of the study for the implementation of one method or another.
The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications. A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used. Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.
This chapter will cover those aspects of systems analysis that are more numerical in scope, dealing with ways to assess the relationship between dynamical models and empirical data. We shall describe techniques that have been found useful in estimating parameters of dynamic models. The chapter will also cover ways in which the modeler can assess how close the model predicts various quantitative and qualitative aspects of the real system under study. Finally we shall describe a method for pinpointing the exact nature of the model’s specification errors in terms of various parts of the model.
In a complex industrial society, work occupies a central role in the lives of all society’s members. It plays a major role in a person’s past, it determines the present, and it moulds the future. Not only does it dictate the quality of life-style, but it also provides a major means of personal identity and self-realization. So it is hardly surprising to find that life within complex organizations can prove to be a great source of stress. Because of this, a great deal of research linking stress and health has been focused on occupational stress (Cherry, 1978; Cooper & Payne, 1978; Cooper & Marshall, 1980; Cooper & Smith, 1986). Although the empirical studies in this field are mounting at a quantum rate in the scholarly journals (Mackay & Cooper, 1987), very little empirical work has been undertaken to understand the dynamics of the stress-health process.
Objective: To examine a path analytical model of potentially causal relationships between national cultural dimensions and rule of law, where press freedom is considered as a mediator.
Method: Three relevant cultural dimensions (Power Distance, Individualism and Masculinity) as suggested by Hofstede (1983) were used as measures of national culture. For measuring Rule of Law, the index constructed by the World Justice Project (2014)was used. Press Freedom was measured with the index constructed by Reporters without Borders (2014). Scores from 68 countries were collected, and a path analytical method
for analysing a potentially causal relation among these three variables was applied.
Results: Power Distance had no direct significant impact on Rule of Law, but a significant relation was found when Press Freedom mediated the relation. Another cultural dimension, Individualism, significantly predicted Rule of Law both directly and mediated by Press Freedom. The third cultural dimension, Masculinity, had both direct and indirect (mediated by Press Freedom) causal relations with Rule of Law.
Conclusion: Press freedom is found in the study to play an important role as a mediator between cultural characteristics and the implementation of rule of law including equal treatment of individuals within societies.
Nesselroade and Molenaar advocate the use of an idiographic filter approach. This is a fixed-effects approach, which may limit the number of individuals that can be simultaneously modeled, and it is not clear how to model the presence of subpopulations. Most important, Nesselroade and Molenaar's proposal appears to be best suited for modeling long time series on a few variables for a few individuals. Long time series are not common in psychological applications. Can it be applied to the usual longitudinal data we face? These are characterized by short time series (four to five points in time), hundreds of individuals, and dozens of variables. If so, what do we gain? Applied settings most often involve between-individual decisions. I conjecture that their approach will not outperform common, simpler, methods. However, when intraindividual decisions are involved, their approach may have an edge.
Die Akzeptanz ist Gegenstand zahlreicher wissenschaftlicher Untersuchungen. Eines der bekanntesten Modelle zur Erklärung von Akzeptanz ist das Technologieakzeptanzmodell (TAM) (Davis, 1989; Davis et al., 1989). Das Modell beschreibt, wie es zur Akzeptanz neuer Informationstechnologie durch den Anwender kommt. In den 30 Jahren seit seiner Einführung ist das Modell vielfach empirisch überprüft und weiterentwickelt worden.
A number of subtle and complex concepts of development are discussed in other chapters of this volume. As other authors note, study designs and data analyses must be carefully executed if concepts are to be properly represented. Kagan, for example (Chapter 2), has pointed to the need to distinguish between connectivity on the one hand and absence of connectivity and emergent phenomena on the other hand. Rutter (Chapter 3) has demonstrated the desirability of distinguishing within- environment determinism from within-person continuity. Fischer et al. (Chapter 5) have raised issues about quantum, or stage, development in contrast to near-continuous development. In almost all chapters there is discussion of how properly to identify stability when, as is inevitably the case, it is found in the company of instability.
There are few, if any, genuine applications of geometry in the behavioral sciences. Factor analysis, or multidimensional scaling methods, cannot be used as examples since the basic concepts of geometry — such as the concepts of ‘line’ or ‘direction’ — do not play any role in the representation. (Typically, the lines obtained in factor analytic or multidimensional representations are all trivial and contain exactly two points.) In the context of the method of triads, this paper develops a geometrical theory based on the concept of the sector Sxy of all the points appearing at least as similar to x as to y. Intuitively, any such sector can be regarded as an abstract half space. Reasonable axioms are given, and it is shown that the resulting structure can be embedded in a ‘linear space’ satisfying the standard incidence axioms of geometry. In such a structure the concepts of ‘subspace’, ‘dimension’ (in various senses), ‘free set’, ‘independence’, etc. can be defined in a satisfactory way. This structure is actually richer than a standard ‘linear space’ in that it also allows ‘parallelism’ and ‘orthogonality’. Possible developments and an actual application of this theory are discussed.
Assessment plays a critical role in meeting instructional needs related to individual differences in student competence. Assessment devices have long been central in determining the educational placement of students with special learning needs. Assessment techniques have also been used to diagnose individual learning problems and to place students in curriculum sequences (Glaser & Nitko, 1971).
Validity generalization refers to whether validity coefficients obtained in prior studies in organizational environments may be used to forecast the value of a validity coefficient in a new but similar organizational environment. Validity coefficients obtained in prior situations are “generalizable” if evidence suggests that they may be employed to forecast the magnitude of a validity coefficient in a new situation. Of perhaps greater importance is the belief that a validation analysis may not be required in the new situation if evidence for validity generalization is extensive. Conversely, a “local” or “situationally specific” validation analysis in the new situation would be required if evidence for validity generalization is unavailable or if the existing evidence suggests a lack of generalization.
The purpose of this study is to develop a scale in order to identify the critical mutlicultural education competencies of teachers. For this reason, first of all, drawing on the knowledge in the literature, a new conceptual framework was created with deductive method based on critical theory, critical race theory and critical multicultural education theory, which includes dimensions of awareness, knowledge, attitude and skill. In accordance with this framework, experimental form consisting of 56 items was submitted to experts for consideration. In accordance with the responses of the experts, content validity rate of the items was identified and the items which were below. 80 level were excluded from the study. The pilot study form consisting of 45 items, was applied to teachers who work preschools, primary and secondary school and the data which was obtained from 421 teachers in total were analyzed. Through the Exploratory Factor Analysis (EFA), a structure consisting of “Awareness”, “Attitude’’, “Knowledge” and “Skill” and 42 items was reached. The relationship between sub-dimensions of the scale was examined and it was observed that the factors were positively and significantly correlated with each other. In this case, it was concluded that scale supports the theory. After the analysis, it was confirmed that the sub-dimensions were the components of a structure called critical multicultural education competency and that together they form a higher structure. It was determined that the goodness of fit index of the model is quite high. Confirmatory Factor Analysis also confirmed the results of EFA. The internal coefficient of concordance was determined as .845 for the whole scale.
Numerous methodologies exist to analyze longitudinal fluency data, including individual growth curve analysis in both observed and latent frameworks, cross-lagged regression to assess interrelations between variables, and multilevel frameworks that consider time as nested within individual. This chapter discusses latent change score (LCS) analysis of oral reading fluency (ORF) and reading comprehension data from a longitudinal sample of 16,000 students from first to fourth grade and compares to linear and nonlinear growth curve analysis. Results highlight the benefits of LCS models compared to traditional linear and nonlinear latent growth models, as well as implications for modeling change with correlated skills.
Affective characteristics, such as attitudes, self-efficacy, and values are impossible to directly observe directly in other humans; they are latent constructs. Latent constructs are variables that we cannot observe directly; instead, we infer their existence through observed variables. This chapter introduces the theoretical concept of the latent variable and the important role it plays in understanding affective characteristics. In addition, we describe the operationalization of a latent construct, the process where instrument developers make both substantive and methodological decisions about the treatment of the observed variables that they are using to model the affective characteristic. This chapter aims to aid the instrument developer in the question or item construction process by highlighting the numerous theoretical and empirical implications of construct definition, measurement, and scaling choices available. This chapter provides both historical perspectives and a review of recent research within the areas of scaling, item construction, and response scale construction.
Correlational methods are often described by contrast with group comparison approaches. In group comparison approaches, as described in Chapter 4, groups are constructed and controls are imposed. Generally, correlational methods are not thought of as being used in controlled studies, but rather in dealing with relationships among phenomena as they exist in natural situations. A correlation can be defined in numerous ways: as the strength of association between phenomena, as the degree to which one phenomenon can be predicted from another phenomenon, or as the degree to which phenomena covary. In a sense, it is a scientific version of the kinds of natural observation in which one relates one thing to another. Underlying these observations, we can usually find some theoretical inference concerning those relationships. For example, the clinician may observe that child abusers are often individuals who have suffered abuse themselves. A formal study of this observation would involve obtaining some response measure of child abuse and of experiencing abuse in the same set of individuals. The measure need only be the presence or absence of the experience. We can then tabulate these data in a contingency arrangement of the type shown in Figure 1. It can be seen there that the high numbers are in those cells that are completely positive or negative for the two phenomena (i.e., abusers with abusive parents and nonabusers with nonabusive parents).
Earlier in this Conference, Cooley indicated that to consider data analysis apart from the research questions being asked is very difficult. Certainly, throughout the course of the Conference, it was evident that analysis in and of itself was rarely criticized or even discussed — even when it was the assigned topic. Instead, criticism was addressed to the content of the research questions. Such an occurrence seems quite natural to me, for I have always sensed a certain amount of symbiosis between the research questions asked and the data-analysis methods used to answer them. Each seems to stimulate the other to new heights: as the questions become more comprehensive and complicated, new techniques are developed to answer them; and likewise, new developments in measurement and observational techniques allow new questions to be addressed.
One of the many nice things that the organizers of this Conference did was to prepare lists of questions on each of the topics for the four speakers. Unfortunately, when they arrived at the area of data analysis, they produced a very short list! At the top of an otherwise empty page was one item: “How can the evaluator best achieve the correct match between the data-analysis techniques and the quality of the data collected (i.e., how can we avoid using a cannon to kill a fly)?”
The scientific basis for managerial decisions is the use of evidence generated from explicit, experiential, and confirmed knowledge. This is a systematic thought process, beginning with the collection of observable facts and then moving to the analysis of these facts to arrive at an adequate explanation of the phenomenon under study. Ideally, scientific data should be gathered under a theoretically informed framework, so that evidence can be derived from the application of data warehousing and data mining techniques. Such evidence-based knowledge can be integrated with practical and experiential knowledge to shed light on the cause-and-effect relationships between the problems and solution sets in the field of health care management.
In this chapter, we introduce structural equation modeling, or the analysis of Linear Structural Relations (LISREL).
In this chapter, we present LISREL’s measurement model in the context of confirmatory factor analysis (CFA).
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