期刊名称：Journal of Modern Applied Statistical Methods
出版年度：2008
卷号：7
期号：2
页码：12
出版社：Wayne State University
摘要：This simulation study investigated the empirical Type I error rates of using the maximum likelihood estimation method and Pearson covariance matrix for multi-group confirmatory factor analysis (MGCFA) of full and strong measurement invariance hypotheses with mixed item format data that are ordinal in nature. The results indicate that mixed item formats and sample size combinations do not result in inflated empirical Type I error rates for rejecting the true measurement invariance hypotheses. Therefore, although the common methods are in a sense sub-optimal, they don’t lead to researchers claiming that measures are functioning differently across groups – i.e., a lack of measurement invariance.
关键词：Multi-Group Confirmatory Factor Analysis; Measurement Invariance; Binary and Ordinal Items
