growcurves (version 0.2.3.6)
Bayesian semi and nonparametric growth curve models that
additionally include multiple membership random effects.
Description
Employs a non-parametric formulation for by-subject random
effect parameters to borrow strength over a constrained number
of repeated measurement waves in a fashion that permits
multiple effects per subject. One class of models employs a
Dirichlet process (DP) prior for the subject random effects and
includes an additional set of random effects that utilize a
different grouping factor and are mapped back to clients
through a multiple membership weight matrix; e.g. treatment(s)
exposure or dosage. A second class of models employs a
dependent DP (DDP) prior for the subject random effects that
directly incorporates the multiple membership pattern.