eRm: predict.ppar – R documentation

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eRm

predict.ppar

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

Examples

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

eRm

Extended Rasch Modeling

v1.0-2

GPL-3

Authors

Patrick Mair [cre, aut], Reinhold Hatzinger [aut], Marco J. Maier [aut], Thomas Rusch [ctb], Rudolf Debelak [ctb]

Initial release

2021-02-11