文章基本信息

标题：Approximate measurement invariance and longitudinal confirmatory factor analysis: concept and application with panel data
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作者：Daniel Seddig ; Heinz Leitgöb
期刊名称：Survey Research Methods
印刷版ISSN：1864-3361
出版年度：2018
卷号：12
期号：1
页码：29-41
语种：English
出版社：European Survey Research Association
其他摘要：This article addresses the approximate approach to assess measurement invariance with (longitudinal) confirmatory factor analysis. Approximate measurement invariance uses zero-mean, small-variance Bayesian priors to allow minor differences in estimated parameters across time, while still maintaining comparability of the underlying constructs. The procedure is illustrated for the first time with panel data on young peoples’ preferences to maximize pleasure and enjoy life. Results indicate whereas the traditional approach of exact measurement invariance failed to establish scalar invariance across time and precluded comparisons of latent means, it was possible to establish approximate scalar invariance. Based on a monitoring procedure for model fit and convergence, a rather small prior variance was deemed sufficient to account for minor deviations of cross-time intercept differences from zero.
其他关键词：confirmatory factor analysis;Bayesian structural equation modeling;approximate measurement invariance;panel data