You can use this program for 3 sets of categorical data for propensity score matching.
            Assume that the data has 3 different categorical variables. You can use it to perform propensity matching of baseline indicator groupings. 
            The matching will make the differences in the baseline data smaller.
            This method was described by Alvaro Fuentes (2022) <doi:10.1080/00273171.2021.1925521>.

Performs Penalized Multivariate Analysis: a penalized
        matrix decomposition, sparse principal components analysis,
        and sparse canonical correlation analysis, described in
        Witten, Tibshirani and Hastie (2009)
        <doi:10.1093/biostatistics/kxp008> and Witten and Tibshirani
        (2009) Extensions of sparse canonical correlation analysis,
        with applications to genomic data
        <doi:10.2202/1544-6115.1470>.

Provides functionality for quality control processing and statistical analysis of mass spectrometry (MS) omics data, in particular proteomic (either at the peptide or the protein level), lipidomic, and metabolomic data, as well as RNA-seq based count data and nuclear magnetic resonance (NMR) data. This includes data transformation, specification of groups that are to be compared against each other, filtering of features and/or samples, data normalization, data summarization (correlation, PCA), and statistical comparisons between defined groups.  Implements methods described in:  Webb-Robertson et al. (2014) <doi:10.1074/mcp.M113.030932>.  Webb-Robertson et al. (2011) <doi:10.1002/pmic.201100078>.  Matzke et al. (2011) <doi:10.1093/bioinformatics/btr479>.  Matzke et al. (2013) <doi:10.1002/pmic.201200269>.  Polpitiya et al. (2008) <doi:10.1093/bioinformatics/btn217>.  Webb-Robertson et al. (2010) <doi:10.1021/pr1005247>.

Monte Carlo based model choice for applied phylogenetics of
    continuous traits. Method described in  Carl Boettiger, Graham Coop,
    Peter Ralph (2012) Is your phylogeny informative? Measuring
    the power of comparative methods, Evolution 66 (7)
    2240-51. <doi:10.1111/j.1558-5646.2011.01574.x>.