baysc: An R package for Bayesian survey clustering

Model-based clustering methods allow a large number of correlated variables to be summarized into underlying patterns, where each pattern describes a cluster and each individual is assigned to a cluster.Example applications include identifying dietary patterns from dietary intake data (Stephenson et al., 2020) and creating profiles of health and development among children (Lanza & Cooper, 2016).Bayesian formulations of such analyses allow the number of clusters to be determined by the data rather than through researcher post-hoc analyses.