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Bioinformatics ; 40(4)2024 Mar 29.
Article in English | MEDLINE | ID: mdl-38485697

ABSTRACT

SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: The R package is freely available at https://cran.r-project.org/package=longmixr with detailed documentation, including a case vignette, at https://cellmapslab.github.io/longmixr/.


Subject(s)
Software , Humans , Cross-Sectional Studies , Cluster Analysis , Surveys and Questionnaires
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