DRM {pcIRT}

Estimation of dichotomous logistic Rasch model (Rasch, 1960)

Description

This function estimates the dichotomous Rasch model by Rasch (1960).

Usage

DRM(data, desmat, start, control)

## S3 method for class 'DRM'
print(x, ...)

## S3 method for class 'DRM'
summary(object, ...)

Arguments

data

Data matrix or data frame; rows represent observations (persons), columns represent the items.

desmat

Design matrix; if missing, the design matrix for a dichotomous Rasch model will be created automatically.

start

starting values for parameter estimation. If missing, a vector of 0 is used as starting values.

control

list with control parameters for the estimation process e.g. the convergence criterion. For details please see the help pages to the R built-in function optim

x

object of class DRM

...

...

object

object of class DRM

Details

Parameters are estimated by CML.

Value

data

data matrix according to the input

design

design matrix either according to the input or according to the automatically generated matrix

logLikelihood

conditional log-likelihood

estpar

estimated basic item parameters

estpar_se

estimated standard errors for basic item parameters

itempar

estimated item parameters

itempar_se

estimated standard errors for item parameters

hessian

Hessian matrix

convergence

convergence of solution (see help files in optim)

fun_calls

number of function calls (see help files in optim)

Author(s)

Christine Hohensinn

References

Fischer, G. H. (1974). Einfuehrung in die Theorie psychologischer Tests [Introduction to test theory]. Bern: Huber.

Rasch, G. (1960). Probabalistic models for some intelligence and attainment tests. Danmarks paedagogiske institut.

Examples

#estimate Rasch model parameters
data(reason)
res_drm <- DRM(reason.test[,1:11])

summary(res_drm)