pairwise (version 0.2.2)

pers: WLE - Rasch Person Parameter

Description

This is the (new) main function for calculation of person estimates based on answering dichotomous or polytomous items according theRasch Model (Rasch, 1960) and Partial Credit Model (Masters, 1982), given the item parameters (object of class "pair" - as a result of pair()) and and the datamatrix (argument daten) containing the person respose vectors (rows), using an WL approach, introduced by Warm (1989).

Usage

pers(itempar, daten = NULL, incidenz = NULL,
    na_treat = NULL, limit = 1e-05, iter = 50,
    tecout = FALSE)

Arguments

itempar

The item parameter prior calculated or estimated. A list object of class "pair" as a result of applying the function pair()) to the data. Or an 'ordinary' "matrix" with

daten

A "matrix" (or "data.frame") optionaly with named colums (names of items) and named rows (Persone IDs). This argument can be left empty when the argument itempar (above) is of class "pair". daten

incidenz

This argument is only relevant when items are assigned to different booklets. For such a booklet-design a "matrix" should be assigned to this argument with the same dimensions like daten, containig 0 and 1 integer codes,

na_treat

optionaly an integer (vector) defining the type of treatment to missing responses in the argument daten. If set to na_treat=NULL (default) missing responses are treated as missings and the respective person is assigned to

limit

numeric giving the limit at which accuracy the WL-algorithm stops.

iter

numeric giving the maximum numer of iteration to perform.

tecout

logical default set toFALSE. If set to TRUE the result will be a (very) long list with estimation details for every case in daten. In case of a booklet-design the list entrys will be divided by "booklet".

Value

• An object of class c("pers", "data.frame") or a (very long) "list" (when setting on techout=TRUE) containing the person parameters.

Details

no detail in the moment.

References

Masters, G. (1982). A rasch model for partial credit scoring. Psychometrika, 47(2), 149–174.

Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen: Danmarks pædagogiske Institut.

Warm, T. A. (1989). Weighted likelihood estimation of ability in item response theory. Psychometrika, 54(3), 427–450.

Examples

############
data(sim200x3)
result <- pers(itempar=pair(sim200x3))
summary(result)