sMCA biplots to visualise complete subsets of incomplete multivariate categorical data.
In order to effortlessly apply the presented methodology in "On subset multiple correspondence analysis for incomplete multivariate categorical data" in Communications in Statistics: Simulation and Computation. 53(11): 5229-5241. (https://doi.org/10.1080/03610918.2023.2173779)
Authors: J Nienkemper-Swanepoel, NJ le Roux & S Gardner-Lubbe Centre for Multi-dimensional data visualisation (MuViSU), Department of Statistics and Actuarial Science, Stellenbosch University.
To start: Open Code > sMCAcalls.R
Users have the option of utilising an example data set, comp.dat.txt, which is a fully observed simulated data set (uniform distribution n=100, p=5). This is accompanied by miss.dat.txt which is the incomplete version of comp.dat.txt with 10% missing values inserted with a missing at random (MAR) mechanism.
Alternatively, incomplete categorical multivariate data sets may be inserted and used in the section for sMCA and construction of biplot in line 27-31.