longmixr

longmixr provides a robust framework for clustering mixed longitudinal data using finite mixture modeling techniques and consensus clustering.

Key Features:

• Mixed Data Type Clustering: longmixr clusters mixed data encompassing binary, categorical, and continuous variables.
• Consensus Clustering: longmixr incorporates consensus clustering to ensure reliable and stable clustering results.
• Longitudinal Data Support: longmixr handles both cross-sectional and longitudinal variables.
• Cluster Exploration and Visualization: longmixr facilitates cluster exploration and visualization through its functionality.

Scientific Applications:

• Patient Stratification: longmixr enables accurate patient stratification in clinical questionnaire analysis through clustering of mixed data types.

Methodology:

longmixr uses finite mixture modeling techniques combined with consensus clustering for robust clustering of longitudinal and cross-sectional data of mixed types.