scholarly journals Evaluating Model Fit in Bayesian Confirmatory Factor Analysis With Large Samples: Simulation Study Introducing the BRMSEA

2017 ◽  
Vol 78 (4) ◽  
pp. 537-568 ◽  
Author(s):  
Huub Hoofs ◽  
Rens van de Schoot ◽  
Nicole W. H. Jansen ◽  
IJmert Kant
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Sample Size ◽  
Simulation Study ◽  
Reliability And Validity ◽  
Model Fit ◽  
Model Complexity ◽  
Large Sample ◽  
Large Samples ◽  
Confirmatory Factor

Bayesian confirmatory factor analysis (CFA) offers an alternative to frequentist CFA based on, for example, maximum likelihood estimation for the assessment of reliability and validity of educational and psychological measures. For increasing sample sizes, however, the applicability of current fit statistics evaluating model fit within Bayesian CFA is limited. We propose, therefore, a Bayesian variant of the root mean square error of approximation (RMSEA), the BRMSEA. A simulation study was performed with variations in model misspecification, factor loading magnitude, number of indicators, number of factors, and sample size. This showed that the 90% posterior probability interval of the BRMSEA is valid for evaluating model fit in large samples ( N≥ 1,000), using cutoff values for the lower (<.05) and upper limit (<.08) as guideline. An empirical illustration further shows the advantage of the BRMSEA in large sample Bayesian CFA models. In conclusion, it can be stated that the BRMSEA is well suited to evaluate model fit in large sample Bayesian CFA models by taking sample size and model complexity into account.

Confirmatory Factor Analysis of the Beck Anxiety Inventory Among Chinese Postgraduates

2018 ◽  
Vol 46 (8) ◽  
pp. 1245-1254
Author(s):  
Yicheng Zhou ◽  
Jing An ◽  
Mingwang Cheng ◽  
Liying Sheng ◽  
Guoqiang Rui ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Reliability And Validity ◽  
Model Fit ◽  
Beck Anxiety Inventory ◽  
Confirmatory Factor ◽  
Competing Models ◽  
Potential Factor ◽  
Analysis Models

We examined the factor structure of the Beck Anxiety Inventory (BAI) with 531 students at 6 universities in Nanjing to evaluate its applicability as a measure of the anxiety of Chinese postgraduates. We performed exploratory factor analysis to identify the potential factor structure of the BAI. We referred to confirmatory factor analysis models from previous studies for model fit. All 7 competing models fitted well with the students' data. The 4-factor structure proposed by Wetherell and Areán yielded the best fit. Results indicate that the BAI has satisfactory reliability and validity among Chinese postgraduates.

The 5-Factor Disgust Scale

2019 ◽  
Vol 35 (3) ◽  
pp. 403-413 ◽  
Author(s):  
Kathrin Eickmeier ◽  
Lisa Hoffmann ◽  
Rainer Banse
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Social Desirability ◽  
Reliability And Validity ◽  
German Language ◽  
Disease Avoidance ◽  
Factor Solution ◽  
Large Samples ◽  
Confirmatory Factor ◽  
Sexual Disgust

Abstract. For years, disgust was conceptualized as a disease-avoidance mechanism. However, research shows that socio-moral or sexual transgressions elicit disgust, too. Until now, no German-language disgust scale has covered all disgust factors discussed in the literature. Here we present an economic Five-Factor Disgust Scale (5-FES; Fünf-Faktoren Ekelskala) along with empirical evidence from three studies corroborating its reliability and validity. Two well-established disgust questionnaires were combined and extended with other disgust-relevant items. Using item reduction and exploratory factor analysis, death-related, moral, food-related, sexual, and pathogen disgust emerged as distinct factors (Study 1: N = 456). Confirmatory factor analysis with two large samples (Study 2: N = 997 and N = 405) demonstrated a good fit of the correlated five-factor solution. The 5-FES correlated weakly with neuroticism, anxiety, and social desirability. A high negative correlation between sexual disgust and sexual openness emerged. Criterion validity was shown using self-reported behaviors (Study 3: N = 203). With food-related disgust comprising items about non-spoiled but exotic foods, a new disgust domain emerged. Results indicate that the 5-FES is a comprehensive and psychometrically sound German-language instrument for the differentiated assessment of disgust propensity.

Probability-Based and Measurement-Related Hypotheses With Full Restriction for Investigations by Means of Confirmatory Factor Analysis

Methodology ◽  
2011 ◽  
Vol 7 (4) ◽  
pp. 157-164
Author(s):  
Karl Schweizer
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Processing ◽  
Latent Variables ◽  
Repeated Measures ◽  
Latent Variable ◽  
Model Fit ◽  
Repeated Measures Data ◽  
Confirmatory Factor ◽  
And Performance

Probability-based and measurement-related hypotheses for confirmatory factor analysis of repeated-measures data are investigated. Such hypotheses comprise precise assumptions concerning the relationships among the true components associated with the levels of the design or the items of the measure. Measurement-related hypotheses concentrate on the assumed processes, as, for example, transformation and memory processes, and represent treatment-dependent differences in processing. In contrast, probability-based hypotheses provide the opportunity to consider probabilities as outcome predictions that summarize the effects of various influences. The prediction of performance guided by inexact cues serves as an example. In the empirical part of this paper probability-based and measurement-related hypotheses are applied to working-memory data. Latent variables according to both hypotheses contribute to a good model fit. The best model fit is achieved for the model including latent variables that represented serial cognitive processing and performance according to inexact cues in combination with a latent variable for subsidiary processes.

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.

Measuring Consumer Motivations to Share Rumors

2014 ◽  
Vol 4 (3) ◽  
pp. 51-67 ◽  
Author(s):  
Subin Sudhir ◽  
Anandakuttan B. Unnithan
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Information Sharing ◽  
Word Of Mouth ◽  
Relationship Management ◽  
Reliability And Validity ◽  
Review Of Literature ◽  
Structured Interviews ◽  
Anxiety Management ◽  
Confirmatory Factor

Rumors are often shared in the marketplace about products, services, brands or organizations; both in the online as well as in the offline scenarios. These rumors get communicated from consumer to consumer in the form of Word of Mouth (WOM). An exhaustive review of literature identified four motivations for consumers to share rumors in the marketplace; which included anxiety management motivation, information sharing motivation, relationship management motivation and self enhancement motivation. The review was not conclusive in identifying any scales for the measurement of these motivations. The article develops a scale for measuring these four motivations. Structured interviews were initially conducted to identify 33 items that motivate a consumer to share rumors. Based on an exploratory factor analysis and confirmatory factor analysis four factors were identified and the final scale retained 21 items. The scale displayed good scores of reliability and validity.

scholarly journals Self-concept in preadolescence: A brief version of AF5 scale

2014 ◽  
Vol 20 (2) ◽  
pp. 151-157
Author(s):  
Pau García-Grau ◽  
Daniel Ayora Pérez ◽  
Ferran Calabuig Moreno ◽  
Vicente Javier Prado-Gascó
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
A Priori ◽  
Reliability And Validity ◽  
Original Model ◽  
Self Concept ◽  
Factorial Structure ◽  
Confirmatory Factor ◽  
Original Scale ◽  
Reduced Scale

The purpose of this study was to analyze the psychometric properties of a brief version of the AF5 questionnaire (García & Musitu, 2001) using exploratory and confirmatory techniques on a preadolescent population in the Valencian community (Spain). The sample was made up of 541 participants between 10 and 12 years old, 55.1% (298) boys and 44.9% (243) girls. After observing the results of different reliability and validity analyses (exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)), it was found that the reduced scale consisting of 20 items showed a similar reliability and validity to the original scale. The factorial structure also fits that of the original model established a priori. According to the results of the study, the use of this diagnostic tool with Spanish children seems justified.

scholarly journals Validation and invariance across gender of the Beliefs About Appearance Scale (BAAS) in a community sample of heterosexual adults in a committed relationship

2018 ◽  
Vol 40 (2) ◽  
pp. 126-135
Author(s):  
Patrícia M. Pascoal ◽  
Maria-João Alvarez ◽  
Magda Sofia Roberto
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Community Sample ◽  
Reliability And Validity ◽  
Two Dimensions ◽  
Original Structure ◽  
Confirmatory Factor Analyses ◽  
Factorial Model ◽  
Confirmatory Factor ◽  
Body Appearance

Abstract Objective To evaluate the psychometric properties of the Beliefs About Appearance Scale (BAAS) in terms of its factorial structure and invariance, reliability, and validity when applied to adults from the community. Methods Participants consisted of 810 heterosexual Portuguese individuals in a committed relationship. As a confirmatory factor analysis did not support the original structure of the BAAS, an exploratory factor analysis was performed. Results A 12-item version was extracted comprising two dimensions: one personal and the other social. The factorial model depicting this bidimensional structure revealed an adequate fit following confirmatory factor analysis. Multigroup confirmatory factor analyses indicated invariance across gender. Concurrent and discriminant validities and internal consistency were estimated and observed to be adequate. Conclusions This shorter measure of the BAAS can accurately assess body appearance beliefs and may be used in different research settings and contexts.

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