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The LASSO on latent indices for regression modeling with ordinal categorical predictors

Hui, Francis; Muller, Samuel; Welsh, Alan


Many applications of regression models involve ordinal categorical predictors. Two common approaches for handling ordinal predictors are to form a set of dummy variables, or employ a two stage approach where dimension reduction is first applied and then the response is regressed against the predicted latent indices. Both approaches have drawbacks, with the former running into a high-dimensional problem especially if interactions are considered, while the latter separates the prediction of the...[Show more]

CollectionsANU Research Publications
Date published: 2020
Type: Journal article
Source: Computational Statistics and Data Analysis
DOI: 10.1016/j.csda.2020.106951
Access Rights: Open Access


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