Version 0.2.3.5 ------------------------------------------------------------------------- FEATURES * updated release on CRAN. * performs Bayesian mixed effects modeling on repeated measures data. * allows a DP prior on a set of subject random effects to borrow strength across subjects for estimation. * simultaneously supports definition of random effects under other than subject groupings with one or more multiple membership (MM) terms. * the dpgrow function performs mixed effects modeling without an MM term (but with a DP prior on the set of subject random effects). * the dpgrowmm function extends dpgrow by allowing for a single MM term under one of three prior formulation options = c("mmi","mmigrp","mmcar"). * the dpgrowmult function extends dpgrowmm by allowing for any number of MM terms, each under one of four prior formulation options = c("mmi","mmigrp","mmcar","mmdp"). * a new ddpgrow function extends dpgrowmm and dpgrowmult by absorbing the MM term inside the subject effects such that each subject parameters their own MM effects. -- prior formulation options = c("car","mvn","ind"). * there are also 3 accompanying graphical accessor functions for the 3 sampling functions to promote easy analysis: * the growplot function produces and plots by-subject growth curves under any user defined grouping. * the trtplot function compares the distribution for the difference in fixed effects means between any two treatment arms. * the effectsplot function compares the mean effect values for an MM term under different prior and model formulations. CHANGES 10/10/2012 ----------- * Fixed errors in effectsplot and ddpEffectsplot functions that render MM random effects plots when user elects option to order by effect size within each plot cell. 11/07/2012 ----------- * Added additional return object, phat, the n x n matrix of pairwise clustering probabilities obtained from sampled clusters. This object may be employed in a deterministic * clustering scheme as an alternative to using the optimal clustering, BigSmin, returned from the least squares clustering algorithm of Dahl (2006). 12/06/2012 ---------- * updated all multivariate normal sampling functions to avoid inverse computation of precision matrix. Now directly draws samples from cholesky decomposition of precision matrix. * updated multiple membership (MM) .cpp models for more efficient posterior sampling of MM random effects * fixed an error that inadvertantly sorted subj.aff (post numerical re-labeling for internal use) such that the labels no longer corresponded with the rows of W.subj.aff 12/11/2012 ---------- * updated all engine functions to pre-compute quadratic products of data matrices and their slices for more efficient computation. 1/24/2013 ---------- * fixed an error when checking user input under function dpgrowmult that accounts for the user not selecting option "mmcar" for any groups. * fixed error in checking for duplicate columns between Z.n and Z.c for generation of random effects design matrix, Z. * fixed an error to reorder "time" variable to be consistent with contiguous by-subject order for growth curve plotting. 3/15/2013 ---------- * fixed an error in ddp.cpp to eliminate use of pow(&int,int), which is not allowed. 3/25/2013 --------- * fixed an error in ddp_quantiles.R to select the correct index when computing the mean covariance matrix, P_mvn[[countmvn]], (for each treatment under "mvn") * fixed an error in dpgrowmm under "multi=TRUE" to create "omega.plus" matrix from Omega * fixed an error in dpgrowmm under option "multi=TRUE" and "option = "mmcar" for computation of the posterior mean of conditionally sampled nv x 1 session effects * fixed a potential error in dpgrowmm where W.subj is set equal to W.subj.aff under all subjects receiving treatment. Coerced W.subj to matrix in the case the user * inputs W.subj.aff as a data.frame object. W.subj is subsequently used in growthCurves function to differentiate a dpgrowmm object (matrix) from a dpgrowmult object (list).