Allows to judge how much the data informed the parameter posterior distributions compared to the prior.
plotPriorPost(
fittedModel,
probitInverse = "mean",
M = 2e+05,
ci = 0.95,
nCPU = 3,
...
)fitted latent-trait or beta MPT model (traitMPT, betaMPT)
which latent-probit parameters (for
traitMPT model) to transform to probability scale. Either
"none", "mean" (simple transformation \(\Phi(\mu)\)), or
"mean_sd" (see probitInverse)
number of random samples to approximate prior distributions
credibility interval indicated by vertical red lines
number of CPUs used for parallel sampling. For large models and many participants, this may require a lot of memory.
arguments passed to boxplot
Prior distributions are shown as blue, dashed lines, whereas posterior distributions are shown as solid, black lines.