Abstract
Accurate clustering of mixed data, encompassing binary, categorical, and continuous variables, is vital for effective patient stratification in clinical questionnaire analysis. To address this need, we present longmixr, a comprehensive R package providing a robust framework for clustering mixed longitudinal data using finite mixture modeling techniques. By incorporating consensus clustering, longmixr ensures reliable and stable clustering results. Moreover, the package includes a detailed vignette that facilitates cluster exploration and visualization.
Original language | English |
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Article number | btae137 |
Journal | Bioinformatics |
Volume | 40 |
Issue number | 4 |
DOIs | |
State | Published - 1 Apr 2024 |