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/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
GrantsNARSAD Young Investigator Grant Deutsche Forschungsgemeinschaft Dr Lisa Oehler Foundation (Kassel, Germany) Bundesministerium fur Bildung und Forschung (BMBF, Federal Ministry of Education and Research) National Institute of Aging of the National Institutes of Health Alzheimer's association award European Union