drm: Estimation of dichotomous logistic Rasch model (Rasch, 1960)

In pcIRT: IRT Models for Polytomous and Continuous Item Responses

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)

pcIRT documentation built on July 16, 2019, 1:02 a.m.