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 (≥ 3.2.2), Rcpp (≥ 0.11.6)|
|Imports:||reshape2 (≥ 1.2.1), Formula (≥ 1.0-0), ggplot2 (≥ 1.0.1)|
|LinkingTo:||Rcpp (≥ 0.11.6), RcppArmadillo (≥ 0.5.000)|
|Suggests:||testthat (≥ 0.9.1)|
|Maintainer:||Terrance Savitsky <tds151 at gmail.com>|
|License:||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]|
|Citation:||growcurves citation info|
|CRAN checks:||growcurves results|
|Windows binaries:||r-devel: growcurves_0.2.4.0.zip, r-release: growcurves_0.2.4.0.zip, r-oldrel: growcurves_0.2.4.0.zip|
|OS X Mavericks binaries:||r-release: growcurves_0.2.4.0.tgz, r-oldrel: growcurves_0.2.4.0.tgz|
|Old sources:||growcurves archive|
Please use the canonical form https://CRAN.R-project.org/package=growcurves to link to this page.