quantiles

summary_quantiles

An output object of class within <code>c("dpgrow", "dpgrowmm")</code>

model.output

Number of total fixed effects, both time-based and nuisance.

Nfixed

Number of total random effects, both time-based and nuisance, all grouped by subject.

Nrandom

Number of unique subjects (on which repeated measures are observed).

Nsubject

Number of subjects, <code>P.aff</code>, receiving multiple membership effects

Nsubj.aff

Number of multivariate MM effects.  Defaults to 1 for univariate MM if left blank.

Number of multiple membership effects for each entry in "Nmv".  May be left blank for univariate MM.

Nsession


Inputs MCMC samples for model parameters and constructs c(2.5%,50%,97.5%) quantile summaries.


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.

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summary_quantiles: Produce quantile summaries of model posterior samples

Description

Usage

Arguments

Value

See Also