rasch.pairwise: Pairwise Estimation Method of the Rasch Model
Description
This function estimates the Rasch model with a minimum chi
square estimation method (cited in Fischer, 2007, p. 544)
which is a pairwise conditional likelihood estimation.Usage
rasch.pairwise(dat, conv = 1e-04, maxiter = 3000, progress = TRUE,
b.init = NULL)
Arguments
dat
An $N$ times $I$ data frame of dichotomous item responses
conv
Convergence criterion
maxiter
Maximum number of iterations
progress
Display iteration progress?
b.init
An optional vector of length $I$ of item difficulties
Value
- An object of class
rasch.pairwise
with following entries - bItem difficulties
- epsExponentiated item difficulties, i.e.
eps=exp(-b)
- iterNumber of iterations
- convConvergence criterion
- datOriginal data frame
- freq.ijFrequency table of all item pairs
- itemSummary table of item parameters
References
Fischer, G. H. (2007) Rasch models.
In C. R. Rao and S. Sinharay (Eds.), Handbook of Statistics,
Vol. 26 (pp. 515-585). Amsterdam: Elsevier.Examples
Run this codedata(data.read)
mod <- rasch.pairwise( data.read )
summary(mod)
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