Posterior predictive model checking of local misfit for Bayesian Confirmatory factor analysis

Author

Chi Hang AuFollow

Preferred Name

Chi Hang Au

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

ORCID

https://orcid.org/0000-0002-6999-0722

Date of Graduation

Summer 2018

Document Type

Thesis

Degree Name

Master of Arts (MA)

Department

Department of Graduate Psychology

Advisor(s)

Allison J. Ames

Abstract

Posterior predictive model checks (PPMC) are one Bayesian model-data fit approach. Thus far, PPMC for Confirmatory Factor Analytic applications focused primarily on global fit evaluation, ignoring the nuanced information in local misfit diagnostics. This study developed a PPMC approach for local misfit and applied it to a test-taking motivation scale. If the PPMC approach is effective, fit conclusions derived from the PPMC approach should be congruent with the fit conclusions derived from the Frequentist approach. Number of item-pairs flagged as misfitting and number of disagreements were computed to evaluate congruence. Congruence is achieved if the number of item-pairs flagged as misfitting is equivalent under the Frequentist and the Bayesian approach and the number of disagreements is zero. Although congruence was not achieved, the present research sets up foundation for future research in PPMC.

Recommended Citation

Au, Chi Hang, "Posterior predictive model checking of local misfit for Bayesian Confirmatory factor analysis" (2018). Masters Theses, 2010-2019. 543.
https://commons.lib.jmu.edu/master201019/543