Structural Equation Modeling (SEM) Workshop for Lecturers and Postgraduate Students

AimThe current study attempted to assess the effect of positive emotion on post-graduate students’ psychological capital (PsyCap) as well as on their academic engagement behavior. Also, the direct relationship between PsyCap and academic engagement behavior was assessed alongside the presence of Stress as a moderating variable between PsyCap and academic engagement behavior amongst post-graduate students in Malaysia.Materials and MethodsA self-administered questionnaire was used for data collection from 373 post-graduate Ph.D. students registered in various universities throughout Malaysia with a non-probabilistic sampling technique. Research respondents belonged to management, humanities, engineering, computer science, and health sciences domains, and they responded through a questionnaire copy. Statistically, structural equation modeling (SEM) was applied to evaluate confirmatory factor analysis (CFA), reliability analysis, validity analysis, measurement model, structural model, and path analysis. Furthermore, the (5000) bootstrapping approach was utilized to test the final model.ResultsFor the hypothesized model, our results confirmed that positive emotions had a positive and significant effect on students’ psychological capita as well as on their academic engagement behavior. Further, PsyCap also had a positive and significant effect on academic engagement behavior. Our results also reported that stress as a moderating variable has a negative and deteriorating effect on the relationship between PsyCap and the academic engagement of students.ConclusionThe study’s findings support the theoretical assumption that positive emotions help individuals generate cognitive resources, which in turn help them manage their engagement behavioral requirements. However, the stress caused by their study needs may deplete their psychological resources, consequently influencing their academic engagement behavior. Interventions like personal coaching/counseling, appropriate follow-up, and flexible goal settings with other measures may help post-graduate students in achieving their daunting tasks.

The association between adverse childhood experiences (ACEs) and depression has been the focus of a number of prevalent studies in recent years—particularly among high-risk youth. Depression remains a significant mental health issue among justice-involved youth. There is a well-established correlation between depressed mood and conduct problems (e.g., conduct disorder and oppositional defiant disorder) during childhood and adolescence, which tends to become more prevalent during adolescence. Studies of justice-involved youth reveal high prevalence rates of depression and other mood disorders. Drawing on the relevant literature, we conducted multigroup structural equation model (SEM) analyses to assess the relationships between experiencing ACEs, sexual assault victimization, and depression among male (n = 226) and female (n = 98) youth entering a post-arrest intake facility in the Florida, U.S.A. juvenile justice system in 2024–2025. The youths averaged 15 years in age, and most were attending middle school or high school. Confirmatory factor analyses (CFAs) were completed to estimate a latent variable labeled depression. Sexual assault victimization and ACEs were hypothesized to be related to each other and were specified as predictors of depression. This trauma/stress experiences and depression model was estimated in two multigroup analyses, across birth gender groups (male or female) and race groups (non-Black or Black) for the youth in this study. The results indicated that there are several notable conclusions from the SEM analyses. First, depression was a scalar invariant in the two multigroup analyses, permitting clearer comparisons of the specified predictors of this construct across groups. Second, for the race-based SEM, experience of sexual assault and the total ACE score were significantly related only in the model for Black youth. The fit of the model was “poorest” among non-Black youth, although even in this case, sexual assault experiences were a significant predictor of depression. Finally, for the gender-based model, sexual assault and ACEs were significant predictors of depression among both male and female youth. Model fit results underscore the important role of abuse trauma and ACEs in understanding these youths’ depression symptoms, and they help contribute to the literature on this topic.

This paper presents the usage of Structural Equation Modelling (SEM) approach in analysing the effects of Building Information Modelling (BIM) technology adoption in improving the reliability of cost estimates. Based on the questionnaire survey results, SEM analysis using SPSS-AMOS application examined the relationships between BIM-improved information and cost estimates reliability factors, leading to BIM technology adoption. Six hypotheses were established prior to SEM analysis employing two types of SEM models, namely the Confirmatory Factor Analysis (CFA) model and full structural model. The SEM models were then validated through the assessment on their uni-dimensionality, validity, reliability, and fitness index, in line with the hypotheses tested. The final SEM model fit measures are: P-value=0.000, RMSEA=0.079<0.08, GFI=0.824, CFI=0.962>0.90, TLI=0.956>0.90, NFI=0.935>0.90 and ChiSq/df=2.259; indicating that the overall index values achieved the required level of model fitness. The model supports all the hypotheses evaluated, confirming that all relationship exists amongst the constructs are positive and significant. Ultimately, the analysis verified that most of the respondents foresee better understanding of project input information through BIM visualization, its reliable database and coordinated data, in developing more reliable cost estimates. They also perceive to accelerate their cost estimating task through BIM adoption.

Purpose – The purpose of this paper is to foster entrepreneurship among students and incubate more start-ups for economic prosperity, universities around the globe are required to play key role in developing overall conducive eco-system for student fraternity. Some previous studies have analysed student entrepreneurship and impact of entrepreneurship courses. However, role of universities as provider and enabler of entrepreneurial environment and its impact on entrepreneurial intent among students has not been studied in a cross-cultural context. Considering this, present study seeks to examine role played by universities in fostering entrepreneurial intention among post-graduate students. Design/methodology/approach – Researcher has taken the framework suggested by Kraaijenbrink et al. (2010) to understand university environment and theory of planned behaviour (Ajzen, 1985) to measure entrepreneurial intention and its antecedents among final year post-graduate management students of India, Malaysia and Singapore. Total sample size is 1,097. Data are analysed with help of exploratory factor analysis, multivariate analysis of variance (MANOVA) and structural equation modelling (SEM). Findings – Two factors emerge out of analysis in relation to university environment and support: first, targeted cognitive and non-cognitive support and second, general educational support. With help of SEM, attempt is made to find relationship between these two factors and entrepreneurial intention. It is found that university environment and support has significantly positive relationship with perceived behavioural control. With help of MANOVA, it is found that there is statistically significant difference between perceived university environment and support factors among students of India, Singapore and Malaysia. With this, for both factors highest mean score is found among students of Malaysia, followed by students of Singapore and India. Originality/value – Study has closely examined role played by university environment and support to foster entrepreneurship among young students. Findings of the study can be used by post-graduate educational institutes to design pedagogy, create enabling entrepreneurship support system and work towards becoming an entrepreneurial university.

Objective To structure one equation model on the relationship of the psychological stress re-sponse and its influential factors of inpatients. Methods This cross-sectional designed study used a stratified-ran-dom-clnster method to recruit 754 inpatients, who were asked to fill out a series of questionnaires assessing hospital stressor, social support, personality, coping style, serf-efficacy, and stressful mental response. Statistic description,analysis of variance (ANOVA), correlations, multiple linear regressions, confirmatory factor analysis, and structural equation model analysis (SEM) were conducted using SPSS 13.0 and LISREL8.70. Results The final model showed good fit index(χ /df = 3.24, CFI, IFI, GFI above 0.90, RMSEA = 0. 056 ). Factors included in the SEM were social support, neuroticism, extraversion, avoidance, resignation, self-efficacy, course of disease and economic status. Self-efficacy significantly impacted mental status;hospital stress can influence patients'mental status direct-ly and indirectly. Conclusion The psychological health status of inpatients can be improved by enhancing posi-tive mediate factors such as self-efficacy and reducing such negative factors as avoidance coping style and disease duration and so on. Key words: Psychological stress; Meditate factors; Self-efficacy; Structural equation model

This article is an attempt to scrutinize the applicability of the widely used statistical technique of Structural Equation Modelling (SEM). SEM is a comprehensive technique to test the model adequacy. SEM is considered as an important advancement in social science research as it combines measurement with substantive theories. It has been observed that many studies pay attention to statistical mechanisation of SEM rather than the assumptions on which it is based. The history of SEM can be traced to Regression Analysis, Path Analysis and Confirmatory Factor Analysis. SEM is popularly applied because of its use in estimating multiple dependence relationships. It is able to measure the unobserved variables, define the model representing the set of relationships and also corrects the measurement error. The technique is commonly applied in disciplines including sociology, psychology and other fields of behavioural science. The availability of various user-friendly software programmes like LISREL, AMOS, EQS, Mx, Mplus and PISTE is an added advantage. However, one should be careful while using SEM for causal inferences. In comparison to other common standard statistical techniques, SEM is based on several assumptions. The technique requires a priori knowledge of all the parameters to be estimated and a substantial amount of data pertaining to covariances, variances and path coefficients. It also requires relationships to be specified in the model. The model inherently assumes temporal precedence and is heavily dependent on researcher’s judgements about exogeneity and directionality. Normality is yet another important assumption of SEM. The mismatch between data characteristics and assumptions imperils inference and accuracy. Like antibiotics are a boon to mankind yet one needs to judiciously use them. Similarly, SEM is a powerful technique however, researchers are suggested to apply cautiously.

Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine. SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis, and path analysis. In this textbook the authors also discuss techniques, such as mixture modeling, that expand the capacity of SEM using a combination of both continuous and categorical latent variables. Features: Basic, intermediate, and advanced SEM topics Detailed applications, particularly relevant for health and medical scientists Topics and examples that are pertinent to both new and experienced SEM researchers Substantive issues in health and medicine in the context of SEM Both methodological and applied examples Numerous figures and diagrams to illustrate the examples As SEM experts situated among clinicians and multidisciplinary researchers in medical settings, the authors provide a broad, current, on the ground understanding of the issues faced by clinical and health services researchers and decision scientists. This book gives health and medical researchers the tools to apply SEM approaches to study complex relationships between clinical measurements, individual and community-level characteristics, and patient-reported scales.

Using quantitative research methods based on Structural Equation Modeling (SEM) in educational research, to analyze the various relationships among variables in the model formed based on the theories studied, few researchers did. This study was conducted to determine the effectiveness of motivation, learning style and discipline of teach on academic achievement Form four students Additional Mathematics in Kuala Terengganu District. The instrument used in this study is based on the School Inventory Learning model developed by Selmes (1987). The item questionnaire in this instrument has been adapted to the investigation investigation. A total of 260 research samples were included in the study, consisting of four forms students in 10 schools in Kuala Terengganu District. Data were analyzed using IBM-SPSS-AMOS (SEM) program version 21.0. SEM analysis consists of two main models: the measurement model and the Structural model. Prior to the SEM test, some adjustment tests were performed to ensure that the tested indicator actually represented the measured construct. Two analyzes in this study are prerequisites that have been met before the SEM analysis is done ie Factor Exploration Analysis (EFA) and Confirmatory Factor Analysis (CFA). The findings indicate that the motivation, learning style and discipline of learning have a positive and significant effect on student achievement in academic achievement. Furthermore, motivation also has a positive and significant impact on the learning discipline, but the learning style has no positive and not significant effect on the learning discipline. Intermediate analysis findings for the learning discipline take place between motivation and academic achievement and do not occur between learning styles and academic achievement. The findings in this study indicate that educators need to instill enthusiasm for students as well as to know their students' learning styles and to ensure that students have a learning discipline, because it can affect student academic achievement.

The Role of Providers in Mental Health Services Offered to American-Indian Youths

Purpose: This study identified the effect of occupational dysfunction on psychological factors of stress response, burnout syndrome, and depression in healthcare workers. Method: Three cross sectional studies were conducted to assess the following relations: 1) occupational dysfunction on stress response (n = 468), 2) occupational dysfunction on burnout syndrome (n = 1142), and 3) occupational dysfunction on depression (n = 687). Personal characteristics were collected through a questionnaire (such as age, gender, and job category, opportunities for refreshment, time spent on leisure activities, and work relationships) as well as the Classification and Assessment of Occupational Dysfunction (CAOD). Furthermore, study 1 included the Stress Response Scale-18 (SRS-18), study 2 used the Japanese Burnout Scale (JBS), and study 3 employed the Center for Epidemiological Studies Depression Scale (CES-D). The Kolmogorov–Smirnov test, confirmatory factor analysis (CFA), exploratory factor analysis (EFA), and path analysis of structural equation modeling (SEM) analysis were used in all of the studies. EFA and CFA were used to measure structural validity of four assessments; CAOD, SRS-18, JBS, and CES-D. For examination of a potential covariate, we assessed the correlation of the total score of CAOD and personal factors in all studies. Moreover, direct and indirect effects of occupational dysfunction on stress response (Study 1), burnout syndrome (Study 2), and depression (Study 3) were also analyzed. Results: CAOD had 16 items and 5 factors. SRS-18 had 18 items and 3 factors, JBS had 17 items and 3 factors, CES-D had 20 items and 4 factors. All studies found that there were significant correlations between the CAOD total score and the personal factor that included opportunities for refreshment, time spent on leisure activities, and work relationships (p&lt;0.01). The causal sequence model results suggest that the classification of occupational dysfunction had positive causal effects on the stress response (RMSEA = 0.058, CFI = 0.951, and TLI = 0.947), burnout syndrome (RMSEA = 0.074, CFI = 0.922, and TLI = 0.915), and depression (RMSEA=0.059, CFI=0.926, TLI=0.920). Moreover, the positive effect of external covariates include opportunities for refreshment, time spent on leisure activities, and work relationships on occupational dysfunction. Conclusion: The classification of occupational dysfunction indicated a possibility of increase in the stress response, burnout syndrome, and depression in healthcare workers. Furthermore, occupational dysfunction affected personal factors including opportunities for refreshment, time spent on leisure activities, and work relationships. Therefore, it is necessary to adopt occupational therapy strategies to prevent this problem.

To use structural equation modeling in testing the construct validity of the questionnaire on the first sexual intercourse among young adolescents. Previously created questionnaire for the estimation of different factors influencing the intention to engage in the first sexual intercourse was validated. The data were gathered anonymously from a nationally representative sample of 1217 elementary school pupils aged 14-15 in Slovenia. The construct validity was determined by the structural equation modeling, LISREL 8.7. The reliability of the questionnaire was satisfactory (Cronbach alpha=0.73). Using the structural equation modeling analyses, the fit between empirical and theoretical models was confirmed, with 18 variables (17 independent and 1 dependent) for 6 latent indicators (5 external and 1 internal). The measures of goodness of fit were chi2(80)=57.040; P=0.976; the root mean square error of approximation was <0.001; the root mean square residual was 0.0249; the goodness of fit index was 0.994; the adjusted goodness of fit index was 0.988; the normed fit index was 0.993; and the relative fit index was 0.986. The instrument explained 34% of the variance in behavior intention. The construct validity of the questionnaire on the intention to engage in the first sexual intercourse among young adolescents was satisfactory. This questionnaire could be a useful tool in health promotion programs.

Background: Telomere length (TL) maintenance plays an important role in bladder cancer (BC) and prognosis. However the manifold influence of everyday life exposures and genetic traits on leucocyte TL (LTL), is not fully elucidated. Methods: Within the framework of a hospital-based case (n = 96)/control (n = 94) study (all Caucasian males), we investigated the extent to which LTL and BC risk were modulated by genetic polymorphisms and environmental and occupational exposures. Data on lifetime smoking, alcohol and coffee drinking, dietary habits and occupational exposures, pointing to aromatic amines (AAs) and polycyclic aromatic hydrocarbons (PAHs) were collected. Structural equation modelling (SEM) analysis appraised this complex relationships. Results: The SEM analysis indicates negative direct links (p < 0.05) between LTL with age, DNA adducts, alcohol and NAT2, and positive ones with coffee, MPO and XRCC3; and between BC risk (p < 0.01) with cigarettes, cumulative exposure to AAs and coffee, while are negative with LTL and age. There was evidence of indirect effects (p < 0.05) on BC risk, probably via LTL reduction, by age and NAT2 (positive link), MPO and XRCC3 (negative link). Conclusions: Our study supports evidence that LTL attrition is a critical event in BC. The new finding that LTL erosion depends on some preventable everyday life exposures genetically modulated, opens new perspectives in BC prevention.

The ultimate goal of brain connectivity studies is to propose, test, modify, and compare certain directional brain pathways. Path analysis or structural equation modeling (SEM) is an ideal statistical method for such studies. In this work, we propose a two-stage unified SEM plus GLM (General Linear Model) approach for the analysis of multisubject, multivariate functional magnetic resonance imaging (fMRI) time series data with subject-level covariates. In Stage 1, we analyze the fMRI multivariate time series for each subject individually via a unified SEM model by combining longitudinal pathways represented by a multivariate autoregressive (MAR) model, and contemporaneous pathways represented by a conventional SEM. In Stage 2, the resulting subject-level path coefficients are merged with subject-level covariates such as gender, age, IQ, etc., to examine the impact of these covariates on effective connectivity via a GLM. Our approach is exemplified via the analysis of an fMRI visual attention experiment. Furthermore, the significant path network from the unified SEM analysis is compared to that from a conventional SEM analysis without incorporating the longitudinal information as well as that from a Dynamic Causal Modeling (DCM) approach.

Socioeconomic status (SES) is inversely related to health status. Disparities in health status among races and ethnic groups are partly attributable to differences in SES, but the indirect pathways by which SES may influence health status are not widely studied. Using the Health and Retirement Study (HRS) data, this dissertation examined the pathways by which SES, via social, psychological, and behavioral factors predicted physical impairment and overnight hospitalization, and asked whether these indirect relationships differed by race/ethnicity. The HRS is a nationally representative multistage area probability sample administered biennially to respondents over the age of 51 and their spouses. Data collected between 2002 and 2010, covering five waves of the original HRS cohort born between the years 1931 and 1941, were used. Two analysis approaches, Structural Equation Modeling (SEM) and Reconstructability Analysis (RA), were used. Adjustments for the complex survey design were made in the SEM analysis, whereas, data were matched for the RA method using propensity scores. Results of the SEM analyses supported most of the hypothesized indirect relationships between SES variables and physical impairment via social and psychological factors, but the indirect effect of SES on physical impairment via behavioral factors was weak. Multiple group analyses of path equality using nested chi-square tests indicated that the indirect effect of SES on physical impairment status did not vary by race/ethnicity. Social, psychological and behavioral factors were weakly related to overnight hospitalization, and SES was not indirectly related to overnight hospitalization. While these results supported several hypothesized indirect relationships between SES variables and physical health status, the indirect effect sizes were small. However, because this study examined predictive paths across groups rather than compare mean differences, and because indirect effects are products of individual path coefficients, small effect sizes are not uncommon in mediation analysis. Moreover, over a lifetime, small effects may gradually add up increasing group differences in health status with greater benefits accruing to higher SES individuals via social and psychological factors, as observed in this study. The RA results showed that indirect relationships between SES and physical impairment were similar across races/ethnicities for identical variables with a few exceptions. In several cases, however, selected SES variables related to social and psychological variables were different for different groups. Cross-sectional indirect relationships were stronger than longitudinal indirect relationships. As in the SEM study, SES was not related to physical impairment via behavioral factors; and, across groups, SES was also

PurposeThe purpose of this paper is threefold: developing an effectiveness communication model for a city rotary event. Empirical validation of the new effectiveness model based on a city cultural festival event to explore the similarity and difference of perception change on event attendance. Providing a structural equation modeling (SEM) analysis of communication model for both professional event organizers and PCO guidelines when determining an event’s marketing strategy priorities.Design/methodology/approachThe authors use SEM to verify the relationship between variables, and path coefficient comparison analysis which was adapted for model verification and hypothesis testing. Analytical methods included reliability analysis, descriptive statistical analysis, HotellingT2-test, SEM analysis.FindingsThis result demonstrates that attendee increased their emotion, attitude, city brand image as result of the event activities, and positive event emotions have the highest influence toward to a positive city’s brand emotion. A positive city brand emotion especially has the second highest influence on attendee next event retentions. A positive city brand emotion will lead to a positive city brand attitude, but city brand attitudes will not have a positive impact on retentions.Originality/valueThe contribution and value of this study is that the authors established a new effectiveness communication model which introduce the city branding concept into the research. The study provides empirical evidence of the effectiveness illustrations of the application in the communication model. The research meets the objective in this effectiveness communication model. It illustrates the directions for how an event should be designed in order to create a positive city brand attitude for retention.