rpf.logprob function

Map an item model, item parameters, and person trait score into a probability vector

Note that in general, exp(rpf.logprob(..)) != rpf.prob(..) because the range of logits is much wider than the range of probabilities due to limitations of floating point numerical precision. methods

rpf.logprob(m, param, theta)

Arguments

• m: an item model
• param: item parameters
• theta: the trait score(s)

Returns

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.

Examples

i1 <- rpf.drm()
i1.p <- rpf.rparam(i1)
rpf.logprob(i1, c(i1.p), -1)   # low trait score
rpf.logprob(i1, c(i1.p), c(0,1))    # average and high trait score