predict.ppar {eRm}

Predict methods

Description

Returns data matrix based on model probabilites. So far implemented for dichotomous models only.

Usage

## S3 method for class 'ppar'
predict(object, cutpoint = "randomized", ...)

Arguments

object

Object of class ppar (from person.parameter()).

cutpoint

Either single integer value between 0 and 1 or "randomized" for randomized 0-1 assignment (see details)

...

Additional arguments ignored

Details

A randomized assignment implies that for each cell an additional random number is drawn. If the model probability is larger than this value, the person gets 1 on this particular item, if smaller, 0 is assigned. Alternatively, a numeric probability cutpoint can be assigned and the 0-1 scoring is carried out according to the same rule.

Value

Returns data matrix based on model probabilities

Author(s)

Patrick Mair, Reinhold Hatzinger

See Also

gofIRT.ppar

Examples

#Model-based data matrix for RSM
res <- RM(raschdat2)
pres <- person.parameter(res)
predict(pres)