rpf.logprob: Map an item model, item parameters, and person trait score into a
probability vector
Description
Note that in general, exp(rpf.logprob(..)) !=
rpf.prob(..) because the range of logits is much wider
than the range of probabilities.
Arguments
m
an item model
param
item parameters
theta
the trait score(s)
Value
a vector of probabilities. For dichotomous items,
probabilities are returned in the order incorrect,
correct. Although redundent, both incorrect and correct
probabilities are returned in the dichotomous case for
API consistency with polytomous item models.