Calculate posterior for one item given score, difficulty and prior

`posterior(score, tau, prior, qp, scale)`

## Arguments

- score
Integer, either 0 (fail) and 1 (pass)

- tau
Numeric, difficulty parameter

- prior
Vector of prior values on quadrature points `qp`

- qp
vector of equally spaced quadrature points

- scale
expansion relative to the logit scale

## Value

A vector of length `length(prior)`

## Details

This function assumes that the difficulties have been estimated by
a binary Rasch model, e.g. by `rasch.pairwise.itemcluster()`

of
the `sirt`

package.

## Author

Stef van Buuren, Arjan Huizing, 2020