Bayesian semiparametric growth curve models that additionally include multiple membership random effects.


[Up] [Top]

Documentation for package ‘growcurves’ version 0.1.1

Help Pages

growcurves-package Bayesian semiparametric growth curve models with employment of multiple membership random effects.
datbrghtterms BRIGHT BDI depressive symptom data with (G = 4) session groups divided into separate MM terms.
datsim Repeated measures for two groups of subjects drawn from mmcar model with no nuisance covariates
datsimcov Repeated measures for two groups of subjects drawn from mmcar model with 2 nuisance covariates
datsimmult Repeated measures for two groups of subjects with two multiple membership (MM) terms
dpgrow Bayesian semiparametric growth curve models.
dpgrow.default Bayesian semiparametric growth curve models.
dpgrowmm Bayesian semiparametric growth curve models with employment of multiple membership random effects.
dpgrowmm.default Bayesian semiparametric growth curve models with employment of multiple membership random effects.
dpgrowmult Bayesian semiparametric growth curve models under employment of more-than-'1' multiple membership random effects (block) term.
dpgrowmult.default Bayesian semiparametric growth curve models under employment of more-than-'1' multiple membership random effects (block) term.
dpPost Run a Bayesian mixed effects model for by-subject random effects with DP prior
effectsplot Plot comparison of Effect parameters of a Multiple membership (MM) term under varied prior formulations
get.mf Produce fixed and random effects design matrices from single formula input
getmf Produce fixed and random effects design matrices from single formula input
growcurves Bayesian semiparametric growth curve models with employment of multiple membership random effects.
growplot Plot by-subject and by-group growth curves
growthCurve Within subject model-predicted growth curve
lgmPost Run a Bayesian mixed effects model for by-subject random effects with an independent Gaussian prior
mcmcPlots generate plots of model(s) posterior results
mmC Bayesian mixed effects model with a DP prior on by-subject effects and CAR prior on a set of multiple membership effects
mmCplusDpPost Bayesian mixed effects model with a DP prior on by-subject effects and CAR prior on a set of multiple membership effects
mmI Bayesian mixed effects model with a DP prior on by-subject effects and zero mean independent Gaussian priors on multiple membership effects
mmIgroup Bayesian mixed effects model with a DP prior on by-subject effects and use of group means for multiple membership effects
mmIgroupDpPost Bayesian mixed effects model with a DP prior on by-subject effects and use of group means for multiple membership effects
mmIplusDpPost Bayesian mixed effects model with a DP prior on by-subject effects and zero mean independent Gaussian priors on multiple membership effects
mmmultPost Bayesian mixed effects model with a DP prior on by-subject effects and more than one multiple membership random effects term
package-growcurves Bayesian semiparametric growth curve models with employment of multiple membership random effects.
plot.dpgrow Produce model plots
plot.dpgrowmm Produce model plots
plot.dpgrowmult Produce model plots
plotmcmc generate plots of model(s) posterior results
quantiles Produce quantile summaries of model posterior samples
relabel Relabel user vector input to sequential numerical
samples Produce MCMC samples for model parameters
samples.dpgrow Produce samples of MCMC output
samples.dpgrowmm Produce MCMC samples for model parameters
samples.dpgrowmult Produce samples of MCMC output
summary.dpgrow S3 functions of dpgrow
summary.dpgrowmm S3 functions of dpgrowmm
summary.dpgrowmult S3 functions of dpgrowmult
summary_quantiles Produce quantile summaries of model posterior samples
trtplot Plot comparison of Mean Effects for Any Two Treatments
XZ generate fixed and random design matrices, X and Z
XZcov generate fixed and random design matrices, X and Z