Title: Analysing observed categorical data in SPSS AMOS: a Bayesian approach

Authors: Hongwei Yang; Lihua Xu; Mark Malisa; Menglin Xu; Qintong Hu; Xing Liu; Hyungsoo Kim; Jing Yuan

Addresses: University of West Florida, 11000 University Pkwy, Pensacola, FL 32514, USA ' Orange County Public Schools, 445 W. Amelia St., Orlando FL 32801, USA ' University of West Florida, 11000 University Pkwy, Pensacola, FL 32514, USA ' Ohio State University, 29 W Woodruf Ave., Columbus, OH, 43210, USA ' Shandong University of Science and Technology, No. 579 QianWanGang Rd., Qingdao, Shandong, 266590, China ' Eastern Connecticut State University, 83 Windham Street, Willimantic, CT 06226, USA ' University of Kentucky, 316 FB Family Sciences University of Kentucky, Lexington, KY 40506, USA ' Guangxi Normal University, Guilin, Guangxi 541003, China

Abstract: This study has a didactic purpose to help applied investigators and practitioners to understand the roles of observed categorical data (OCD) in structural equation modelling (SEM) and the appropriate ways of analysing such data under SPSS AMOS. To that end, the study reviews types of OCD (nominal, ordinal, dichotomous and polytomous) and their incorporation into SEM under AMOS to play different roles. The study presents two applications from the health and retirement study where Bayesian statistical inference is used to analyse one set of OCD variables serving as endogenous variables with/without groups created by another OCD variable. Besides, the study demonstrates the typical ways of summarising, reporting and interpreting the results from Bayesian statistics, and compares AMOS with several other SEM programmes (Mplus, R lavaan, Stata and SAS PROC CALIS) on handling OCD. The study concludes with summaries of the findings for its intended audience.

Keywords: structural equation modelling; SEM; multi-group analysis; Bayesian statistics; SPSS AMOS; categorical data analysis; Mplus; R lavaan; Stata; SAS PROC CALIS; health and retirement study; HRS.

DOI: 10.1504/IJQRE.2022.129792

International Journal of Quantitative Research in Education, 2022 Vol.5 No.4, pp.399 - 430

Accepted: 24 Mar 2022
Published online: 28 Mar 2023 *

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