Methodological review demonstrates latent variable modeling frameworks across discrete and continuous data types, highlighting analytical foundations and structural relations.
Basic ideas foundations factor analysis and latent profile analysis latent class and latent trait analysis - binary response data, polysomous response data mixed response variables posterior analysis linear structural relations methods comparison with principle components analysis synoptic view.
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Tatsuoka et al. (1989) studied this question.
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