A Restricted Latent Class Model with Polytomous Attributes and Respondent-Level Covariates
| Autor: | Wayman, Eric Alan, Culpepper, Steven Andrew, Douglas, Jeff, Bowers, Jesse |
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| Rok vydání: | 2024 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | We present an exploratory restricted latent class model where response data is for a single time point, polytomous, and differing across items, and where latent classes reflect a multi-attribute state where each attribute is ordinal. Our model extends previous work to allow for correlation of the attributes through a multivariate probit and to allow for respondent-specific covariates. We demonstrate that the model recovers parameters well in a variety of realistic scenarios, and apply the model to the analysis of a particular dataset designed to diagnose depression. The application demonstrates the utility of the model in identifying the latent structure of depression beyond single-factor approaches which have been used in the past. Comment: 37 pages, 1 figure, 7 tables; changed title, fixed one typo, improved accessibility, and made stylistic adjustments |
| Databáze: | arXiv |
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