scholarly journals Explicating the South African Psychological Ownership Questionnaire’s confirmatory factor analysis model fit: A Bayesian structural equation modelling approach

2019 ◽  
Vol 45 ◽  
Author(s):  
Pieter Schaap
Keyword(s):  
South African ◽  
Structural Equation ◽  
Measurement Model ◽  
Model Fit ◽  
Psychological Ownership ◽  
Fit Indices ◽  
Chi Square ◽  
Equation Modelling ◽  
Confirmatory Factor ◽  
Global Fit

Orientation: The rigid application of conventional confirmatory factor analysis (CFA) techniques, the overreliance on global model fit indices and the dismissal of the chi-square statistic appear to have an adverse impact on the research of psychological ownership measures.Research purpose: The purpose of this study was to explicate the South African Psychological Ownership Questionnaire’s (SAPOS’s) CFA model fit using the Bayesian structural equation modelling (BSEM) technique.Motivation for the study: The need to conduct this study derived from a renewed awareness of the incorrect use of the chi-square statistic and global fit indices of CFA in social sciences research.Research approach/design and method: The SAPOS measurement model fit was explicated on two study samples consisting, respectively, of 712 and 254 respondents who worked in various organisations in South Africa. A Bayesian approach to CFA was used to evaluate if local model misspecifications were substantive and justified the rejection of the SAPOS model.Main findings: The findings suggested that a rejection of the SAPOS measurement model based on the results of the chi-square statistic and global fit indices would be unrealistic and unfounded in terms of substantive test theory.Practical/managerial implications: BSEM appeared to be a valuable diagnostic tool to pinpoint and evaluate local CFA model misspecifications and their effect on a measurement model.Contribution/value-add: This study showed the importance of considering local misspecifications rather than only relying the chi-square statistic and global fit indices when evaluating model fit.

scholarly journals Determinants of Employees’ Knowledge Sharing Intention through Perspectives of Social Capital, Emotion and Motivation

2016 ◽  
Author(s):  
Canan Nur Karabey ◽  
Isil Karabey
Keyword(s):  
Social Capital ◽  
Knowledge Sharing ◽  
Self Efficacy ◽  
Sense Of Belonging ◽  
Structural Equation ◽  
Measurement Model ◽  
Relational Capital ◽  
Shopping Malls ◽  
Equation Modelling ◽  
Confirmatory Factor

The aim of this study is to investigate the factors that determine employee’s knowledge sharing intention through the perspectives of social capital, emotion and motivation. The impacts of individual factors, namely social capital, enjoyment in and fear for knowledge sharing, sense of belonging and knowledge sharing self-efficacy on employee’s intention to share knowledge with colleagues are examined. In order to test the hypotheses regarding the relationships among aforementioned variables, data were gathered through question forms from 267 employees working at two shopping malls in a province of Turkey. First, confirmatory factor analysis was applied to data on LISREL 8.7 software. Second, the validity of the measurement model was examined and last, anticipated relationships among variables were investigated through path analysis in structural equation modelling. The results stated that fear for sharing knowledge affected intention negatively while enjoyment in sharing knowledge and knowledge sharing self-efficacy affected intention positively. Also, relational capital was not found to impact intention to share knowledge via fear and enjoyment. On the other hand, sense of belonging impacted intention merely through enjoyment in sharing knowledge.

Employability of fresh engineering graduates in India

2019 ◽  
Vol 62 (1) ◽  
pp. 47-63
Author(s):  
Saitab Sinha ◽  
Piyali Ghosh ◽  
Ashutosh Mishra
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Past Research ◽  
Measurement Model ◽  
Model Fit ◽  
Mediation Model ◽  
Multiple Stakeholders ◽  
Content Type ◽  
Confirmatory Factor

Purpose The purpose of this paper is to examine whether satisfaction of employers with skill competencies of fresh engineering graduates (EGs) in India is impacted by their expectations and perceptions. Applying Expectation Confirmation Theory (ECT), the authors have also proposed and tested whether such effects on employers’ satisfaction are mediated by (dis)confirmation. Design/methodology/approach Data were collected through a survey of employers’ representatives using a structured questionnaire. The proposed mediation model has been tested on a sample of 284 with Confirmatory Factor Analysis by applying structural equation modelling in AMOS. Findings The structural model has been constructed with six latent constructs in accordance with extant literature. Excluding some observed variables, the structural model was found to have a good model fit. The measurement model is in accordance with ECT. Three of the four independent variables (two related to employers’ expectations and one to employers’ perception) exert significant influence on employers’ satisfaction, with (dis)confirmation as a mediator. Practical implications Industry–academia partnerships need to be an integral feature of any curriculum to bridge the gap between course curricula on one hand and employers’ expectations and perceptions on the other. Originality/value Past research on employability of EGs has mostly explored a direct association between employers’ perception and satisfaction. The authors study contributes to literature by examining the role of employers’ expectations in addition to their perception as precursors of their satisfaction, using the framework of ECT. Outcomes reported are of relevance to multiple stakeholders in technical education.

Should We Use F-Tests for Model Fit Instead of Chi-Square in Overidentified Structural Equation Models?

2018 ◽  
Vol 23 (3) ◽  
pp. 487-510 ◽  
Author(s):  
Daniel McNeish
Keyword(s):  
Data Model ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Structural Equation Models ◽  
Small Sample ◽  
Model Fit ◽  
Ratio Test ◽  
Fit Indices ◽  
Chi Square ◽  
Advantages And Disadvantages

Debate continues about whether the likelihood ratio test ( T ML) or goodness-of-fit indices are most appropriate for assessing data-model fit in structural equation models. Though potential advantages and disadvantages of these methods with large samples are often discussed, shortcomings concomitant with smaller samples are not. This article aims to (a) highlight the broader small sample issues with both approaches to data-model fit assessment, (b) note that what constitutes a small sample is common in empirical studies (approximately 20% to 50% in review studies, depending on the definition of “small”), and (c) more widely introduce F-tests as a desirable alternative than the traditional T ML tests, small-sample corrections, or goodness-of-fit indices with smaller samples. Both goodness-of-fit indices and comparing T ML to a chi-square distribution at smaller samples leads to overrejection of well-fitting models. Simulations and example analyses show that F-tests yield more desirable statistical properties—with or without normality—than standard approaches like chi-square tests or goodness-of-fit indices with smaller samples, roughly defined as N < 200 or N: df < 3.

Conceptualization and validation of the Neighbourhood Cohesion Index using exploratory structural equation modelling

2020 ◽  
Author(s):  
Allison Ross ◽  
Mark Searle
Keyword(s):  
Social Capital ◽  
Sense Of Community ◽  
Structural Equation Modelling ◽  
Structural Equation ◽  
Factor Model ◽  
Model Fit ◽  
Equation Modelling ◽  
Confirmatory Factor ◽  
Phoenix Metropolitan Area ◽  
Three Factor

Abstract The Neighbourhood Cohesion Index (NCI) is a popular scale used to measure social capital and cohesion at the neighbourhood level. Despite its prevalent use, discrepancies exist with regard to the factor structure of the scale. We explore a two- versus three-factor conceptualization of the NCI by comparing results of confirmatory factor analysis and exploratory structural equation modelling (ESEM) for each model among a representative sample of adults (n = 798) in the Greater Phoenix Metropolitan Area (AS, USA). The ESEM three-factor model with the subscales of attraction, neighbouring, and sense of community was the best model fit. This three-factor model proved to be invariant across age, gender, health, and race within our sample. Given the need to determine consistent definitions and measurement of social capital and cohesion, these findings strengthen and support the use of the NCI as an instrument to measure attraction, neighbouring, and sense of community within neighbourhoods.

scholarly journals Confirmatory factor analysis of the Warwick-Edinburgh Mental Wellbeing Scale among youth in Mexico

2017 ◽  
Vol 62 (1) ◽  
pp. 309-315 ◽  
Author(s):  
Steven Hoffman ◽  
Heidi A Rueda ◽  
Matthew C Lambert
Keyword(s):  
Mental Health ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Model Fit ◽  
Mental Wellbeing ◽  
Fit Indices ◽  
Chi Square ◽  
Confirmatory Factor ◽  
Health Assessments ◽  
Chi Square Test

The internal structure of the Warwick-Edinburgh Mental Wellbeing Scale was evaluated using confirmatory factor analysis for a sample of youth living in Michoacán, Mexico. While the chi-square test of model fit suggested misfit to the data, the alternative fit indices and standardized factor loadings supported the conclusion that the items are adequate and reliable indicators of a single underlying latent factor. The utilization of this strengths-based mental health instrument could help circumvent some of the negativity and stigma inherent in traditional mental health assessments.

Testing robustness, model fit, and measurement invariance of the Student Engagement Scale in an African university context

2017 ◽  
Vol 26 (3) ◽  
pp. 92-102 ◽  
Author(s):  
Tefera Tadesse ◽  
Robyn M Gillies
Keyword(s):  
Student Engagement ◽  
Measurement Invariance ◽  
Undergraduate Students ◽  
Structural Equation ◽  
Factor Model ◽  
Model Fit ◽  
Supporting Evidence ◽  
Equation Modelling ◽  
Confirmatory Factor ◽  
Engagement Scale

This study examined a modified version of the Student Engagement Scale, as adopted from the Australasian Survey of Student Engagement. It did so through examining model fit, predictive validity of the engagement factor, and testing of score reliability and measurement invariance across colleges and class years. Participants were volunteer undergraduate students (n = 536) from two colleges of a large university in Ethiopia. Confirmatory factor analysis using structural equation modelling was used. The results reasonably supported a nine-factor model over other models, and testing of measurement invariance confirmed a good model fit for the nine-factor model across college and class year. Overall, the findings demonstrated supporting evidence for the validity of the nine-factor structure.

scholarly journals The Factors of Selecting Malaysia as Tourist Destination

2019 ◽  
Author(s):  
A. S. A. Ferdous Alam ◽  
Er Ah Choy ◽  
Halima Begum ◽  
Md. Mahmudul Alam ◽  
Chamhuri Siwar
Keyword(s):  
Factor Analysis ◽  
Structural Equation ◽  
Descriptive Statistics ◽  
Model Fit ◽  
Primary Data ◽  
Economic Sector ◽  
Tourist Destination ◽  
Community Factors ◽  
Equation Modelling ◽  
Confirmatory Factor

Tourism is an emerging economic sector for Malaysia. The purpose of this study is an attempt to understand the factors that attract tourists to visit Malaysia. The primary data were collected through questionnaire survey on 735 tourists who visited the state of Melaka, Malaysia. This study used descriptive statistics, confirmatory factor analysis, and structural equation modelling (SEM) in order to analyze and draw the inferences. Model fit was initially tested using the overall fit and regression paths. Then the hypothesized model was analysed and modified based on the results of the analysis to find a better fit of the data and to more adequately describe the relationships between the factors. The study found that several economic, environmental, cultural and community factors have positive significant influence in attracting tourists to Melaka.

A Bootstrap Procedure for Evaluating Goodness-of-Fit Indices of Structural Equation and Confirmatory Factor Models

1989 ◽  
Vol 26 (1) ◽  
pp. 105-111 ◽  
Author(s):  
Paula Fitzgerald Bone ◽  
Subhash Sharma ◽  
Terence A. Shimp
Keyword(s):  
Structural Equation ◽  
Goodness Of Fit ◽  
Factor Models ◽  
Model Fit ◽  
Fit Indices ◽  
Bootstrap Sampling ◽  
Bootstrap Procedure ◽  
Number Of Factors ◽  
Confirmatory Factor ◽  
Competing Models

The authors propose a bootstrap procedure for evaluating the goodness-of-fit indices for structural equation and confirmatory factor models. Monté Carlo simulations are applied to obtain a bootstrap sampling distribution (BSD) for each fit statistic. Then the BSD is used to evaluate model fit. Because the BSD takes into consideration sample size and model characteristics (e.g., number of factors, number of indicators per factor), its application in the proposed procedure makes it possible to compare the fits of competing models. Two previous studies are reanalyzed in illustrating how to implement the proposed procedure.

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