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eRm (version 1.0-1)

predict.ppar: Predict methods

Description

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

Usage

# S3 method for 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

Value

Returns data matrix based on model probabilities

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.

See Also

gofIRT.ppar

Examples

Run this code
# NOT RUN {
#Model-based data matrix for RSM
res <- RM(raschdat2)
pres <- person.parameter(res)
predict(pres)
# }

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