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sirt (version 1.14-0)

rasch.jml.biascorr: Bias Correction of Item Parameters for Joint Maximum Likelihood Estimation in the Rasch model

Description

This function computes an analytical bias correction for the Rasch model according to the method of Arellano and Hahn (2007).

Usage

rasch.jml.biascorr(jmlobj,itemfac=NULL)

Arguments

jmlobj
An object which is the output of the rasch.jml function
itemfac
Number of items which are used for bias correction. By default it is the average number of item responses per person.

Value

A list with following entries A list with following entries

References

Arellano, M., & Hahn, J. (2007). Understanding bias in nonlinear panel models: Some recent developments. In R. Blundell, W. Newey & T. Persson (Eds.): Advances in Economics and Econometrics, Ninth World Congress, Cambridge University Press.

See Also

See rasch.jml.jackknife1 for bias correction based on Jackknife.

See also the bife R package for analytical bias corrections.

Examples

Run this code
#############################################################################
# EXAMPLE 1: Dataset Reading
#############################################################################
data(data.read)
dat <- data( data.read )

# estimate Rasch model
mod <- rasch.jml( data.read  )

# JML with analytical bias correction
res1 <- rasch.jml.biascorr( jmlobj=mod  )
print( res1$b.biascorr , digits= 3 )
  ##        b.JML b.JMLcorr b.analytcorr1 b.analytcorr2
  ##   1  -2.0086   -1.8412        -1.908        -1.922
  ##   2  -1.1121   -1.0194        -1.078        -1.088
  ##   3  -0.0718   -0.0658        -0.150        -0.127
  ##   4   0.5457    0.5002         0.393         0.431
  ##   5  -0.9504   -0.8712        -0.937        -0.936
  ##  [...]

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