A Comparison of Reliability Estimation Based on Confirmatory Factor Analysis and Exploratory Structural Equation Models

2021 ◽  
pp. 001316442110089
Author(s):  
Yuanshu Fu ◽  
Zhonglin Wen ◽  
Yang Wang
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Reliability Estimation ◽  
Model Fit ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Reliability Estimates ◽  
Confirmatory Factor ◽  
Composite Reliability

Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is often found to be substantially better than that of ICM-CFA. The present study first illustrated the method used to estimate composite reliability under ESEM and then compared the difference between ESEM and ICM-CFA in terms of composite reliability estimation under various indicators per factor, target factor loadings, cross-loadings, and sample sizes. The results showed no apparent difference in using ESEM or ICM-CFA for estimating composite reliability, and the rotation type did not affect the composite reliability estimates generated by ESEM. An empirical example was given as further proof of the results of the simulation studies. Based on the present study, we suggest that if the model fit of ESEM (regardless of the utilized rotation criteria) is acceptable but that of ICM-CFA is not, the composite reliability estimates based on the above two models should be similar. If the target factor loadings are relatively small, researchers should increase the number of indicators per factor or increase the sample size.

scholarly journals Statistically Validated Component- and Indicator-Level Requirements for Sustainable Thai Homestay Businesses

2021 ◽  
Vol 13 (2) ◽  
pp. 936
Author(s):  
Nawhath Thanvisitthpon
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Sem Analysis ◽  
Equation Modeling ◽  
Component Level ◽  
Factor Loadings ◽  
Statistical Reliability ◽  
Confirmatory Factor

This research proposes an updated version of homestay indicators for 10 existing component-level homestay requirements. The updated indicators were aimed to replace the decade-old original indicators for Thai homestay businesses. Besides, the 31 original homestay indictors were not statistically validated. In this study, structural equation modeling (SEM) was used to determine the statistical relevancy between the updated homestay indicators and the components. The SEM analysis involved two steps: exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The EFA statistically regrouped the 31 updated indictors by six new homestay components. The six components and 31 updated indicators were further validated by CFA to determine the factor loadings and statistical reliability of the components and indicators. The factor loadings indicate the levels of importance that homestay guests attach to different homestay components and indicators. Therefore, Thai homestay operators should give priority to the components and indicators with high factor loadings.

scholarly journals Examining the ParticipACTION brand using the brand equity pyramid

2018 ◽  
Vol 8 (4) ◽  
pp. 378-396 ◽  
Author(s):  
Alexander Lithopoulos ◽  
Peter A. Dacin ◽  
Tanya R. Berry ◽  
Guy Faulkner ◽  
Norm O’Reilly ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Brand Equity ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Equation Modeling ◽  
Content Type ◽  
Activity Promotion ◽  
Confirmatory Factor

Purpose The brand equity pyramid is a theory that explains how people develop loyalty and an attachment to a brand. The purpose of this study is to test whether the predictions made by the theory hold when applied to the brand of ParticipACTION, a Canadian non-profit organization that promotes active living. A secondary objective was to test whether this theory predicted intentions to be more physically active. Design/methodology/approach A research agency conducted a cross-sectional, online brand health survey on behalf of ParticipACTION. Exploratory factor analysis and confirmatory factor analysis established the factor structure. Structural equation modeling was used to test the hypothesized model. Findings A nationally representative sample of Canadian adults (N = 1,191) completed the survey. Exploratory factor analysis and confirmatory factor analysis supported a hypothesized five-factor brand equity framework (i.e. brand identity, brand meaning, brand responses, brand resonance and intentions). A series of structural equation models also provided support for the hypothesized relationships between the variables. Practical implications Though preliminary, the results provide a guide for understanding the branding process in the activity-promotion context. The constructs identified as being influential in this process can be targeted by activity-promotion organizations to improve brand strength. A strong organizational brand could augment activity-promotion interventions. A strong brand may also help the organization better compete against other brands promoting messages that are antithetical to their own. Originality/value This is the first study to test the brand equity pyramid using an activity-promotion brand. Results demonstrate that the brand equity pyramid may be useful in this context.

scholarly journals Modeling and Analysis of the Motivations of Fast Fashion Consumers in Relation to Innovativeness

2016 ◽  
Vol 16 (4) ◽  
pp. 205-213
Author(s):  
Canan Saricam ◽  
Nazan Erdumlu
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Motivational Factors ◽  
Equation Modeling ◽  
Fast Fashion ◽  
Modeling And Analysis ◽  
Confirmatory Factor ◽  
The Relationship

Abstract In this study, fast fashion concept is investigated in order to understand the motivations of the consumers that make them adopt these products because of their willingness for the innovativeness. The relationship between the motivational factors which were named as “Social or status image” and “Uniqueness” as expressions of individuality, “Conformity” and the willingness for “Innovativeness” is analyzed using a conceptual model. Exploratory factor analysis, confirmatory factor analysis and structural equation modeling were used to analyze and validate the model. The data used for the study was obtained from 244 people living in Turkey. The findings showed that the motivational factors “Social or status image” and “Uniqueness” as expressions of individuality are influential on the consumers’ willingness for “Innovativeness”.

Developing an Instrument for E-Public Services’ Acceptance Using Confirmatory Factor Analysis

2012 ◽  
Vol 24 (3) ◽  
pp. 18-44 ◽  
Author(s):  
Ahmed Alzahrani ◽  
Bernd Carsten Stahl ◽  
Mary Prior
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Technology Acceptance ◽  
Structural Equation ◽  
Large Scale ◽  
Public Services ◽  
Equation Modeling ◽  
Data Sampling ◽  
Potential Cost ◽  
Confirmatory Factor

Governments worldwide spend billions from their allocated IT budgets to deliver convenient electronic services to their citizens. As a result, it is important to encourage citizens to use these services to avoid potential failures. Yet, few empirical studies exist that cover the relevant issues of adoption from the perspective of citizens in developing countries. Moreover, the need for a well-validated instrument to capture citizen adoption of such services is vital, given the vast investment in technology and the potential cost-saving implications. This study integrates elements from the most popular theories, including adoption technology acceptance model (TAM), innovation diffusion theory (IDT), and theory of planned behavior (TPB), in conjunction with web trust models. It develops an instrument to measure citizens’ acceptance of electronic public services by utilizing confirmatory factor analysis (CFA) within the structural equation modeling technique. Findings of a large scale data sampling of citizens in Saudi Arabia indicate that the proposed measurement model is an acceptable fit with the data. Overall, the findings supply a rigorous instrument for measuring citizens’ acceptance of e-public services, providing further insights for researchers and offering policy makers a suitable tool with which to study proposed strategies.

Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review

2006 ◽  
Vol 99 (6) ◽  
pp. 323-338 ◽  
Author(s):  
James B. Schreiber ◽  
Amaury Nora ◽  
Frances K. Stage ◽  
Elizabeth A. Barlow ◽  
Jamie King
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Equation Modeling ◽  
Confirmatory Factor

Investigating the Structure of the Pediatric Symptoms Checklist in the Preschool Setting

2016 ◽  
Vol 35 (5) ◽  
pp. 494-505 ◽  
Author(s):  
Christine DiStefano ◽  
Jin Liu ◽  
Yin Burgess
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Short Form ◽  
School Setting ◽  
Equation Modeling ◽  
Confirmatory Factor ◽  
Psychological Instruments ◽  
Preschool Setting

When using educational/psychological instruments, psychometric investigations should be conducted before adopting to new environments to ensure that an instrument measures the same constructs. Exploratory structural equation modeling and confirmatory factor analysis methods were used to examine the utility of the short form of the Pediatric Symptoms Checklist (PSC-17) in the school setting. Using a sample of 836 preschool children rated by teachers, three factors were identified across both techniques, with factors matching the hypothesized structure of the instrument. The PSC-17 may be an option for use in preschool settings when conducting behavioral and emotional screening.

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