pip: Posterior Inclusion Probabilities

In vICC: Varying Intraclass Correlation Coefficients

Description

Extract the posterior inclusion probabilities (PIP) for either the random intercepts for sigma or the random effects standard deviation for sigma.

Usage

pip(object, ...)

Arguments

object	Ab object of class vicc.
...	Currently ignored.

Value

A data frame.

Note

The PIPs indicate whether the groups differ from the fixed effect, or average, within-group variance. If the PIP is large, this indicates there is high probability that group differs from the common variance. A marginal Bayes factor can be computed as PIP / (1 - PIP), assuming that prior_prob = 0.5.

Examples

# congruent trials
congruent <- subset(flanker, cond == 0)

# subset 25 from each group
dat <- congruent[unlist(tapply(1:nrow(congruent),
                            congruent$id,
                            head, 25)), ]

# fit model
fit <- vicc(y  = dat$rt,
            group = dat$id,
            iter = 250,
            burnin = 10,
            type =  "pick_group")

pip(fit)

vICC documentation built on Dec. 8, 2020, 5:07 p.m.