growcurves: Bayesian semi and nonparametric growth curve models that additionally include multiple membership random effects

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.

Depends: R (≥ 3.0.2), Rcpp (≥ 0.10.6)
Imports: RcppArmadillo (≥ 0.4.000), reshape2 (≥ 1.2.1), scales (≥ 0.2.0), ggplot2 (≥ 0.9.2), Formula (≥ 1.0-0), testthat (≥ 0.8)
LinkingTo: Rcpp (≥ 0.10.6), RcppArmadillo (≥ 0.4.000)
Published: 2014-02-23
Author: Terrance Savitsky
Maintainer: "terrance savitsky" <tds151 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: growcurves citation info
Materials: NEWS
In views: Bayesian
CRAN checks: growcurves results


Reference manual: growcurves.pdf
Package source: growcurves_0.2.3.9.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: growcurves_0.2.3.9.tgz, r-oldrel: growcurves_0.2.3.9.tgz
OS X Mavericks binaries: r-release: growcurves_0.2.3.9.tgz
Old sources: growcurves archive