Latent structure analysis of repeated classifications with dichotomous data

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Abstract
Latent structure models are presented for situations involving repeated, dichotomous classifications as might arise, for example, in panel studies. Procedures for estimation, hypothesis testing and comparisons among alternative models are developed for two or more occasions of measurement. In addition, methods are suggested for multivariate panel studies where two or more variables are each measured repeatedly. The procedures are exemplified with real‐life data sets.

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