Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares

• Published in: Behavior research methods Vol. 48; no. 3; pp. 936 - 949
• Main Author: Li, Cheng-Hsien
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2016
• Subjects: Behavioral Science and Psychology; Chi-Square Distribution; Cognitive Psychology; Data Interpretation, Statistical; Factor Analysis, Statistical; Humans; Least-Squares Analysis; Likelihood Functions; Models, Statistical; Monte Carlo Method; Psychology; Sample Size; Confirmatory factor analysis; Robust estimation; Monte Carlo Simulation; Ordinal data

In confirmatory factor analysis (CFA), the use of maximum likelihood (ML) assumes that the observed indicators follow a continuous and multivariate normal distribution, which is not appropriate for ordinal observed variables. Robust ML (MLR) has been introduced into CFA models when this normality as...