#3215. Model-based recursive partitioning of extended redundancy analysis with an application to nicotine dependence among US adults

September 2026publication date
Proposal available till 12-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Statistics and Probability;
Arts and Humanities (miscellaneous);
Psychology (all);
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Abstract:
Extended redundancy analysis (ERA) is used to reduce multiple sets of predictors to a smaller number of components and examine the effects of these components on a response variable. ERA is currently unable to consider such covariate-dependent heterogeneity to examine whether the model parameters vary across subgroups differentiated by covariates. To address this issue, the research combines ERA with model-based recursive partitioning in a single framework. This combined method, MOB-ERA, aims to partition observations into heterogeneous subgroups recursively based on a set of covariates while fitting a specified ERA model to data. It produces a tree diagram that aids in visualizing a hierarchy of partitioning covariates, as well as interpreting their interactions and yields different directional relationships between three predictor sets and nicotine dependence.
Keywords:
covariate-dependent heterogeneity; decision tree; extended redundancy analysis; model visualization; model-based recursive partitioning

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