drm function

Estimation of dichotomous logistic Rasch model (Rasch, 1960)

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

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

Returns

• 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)

Details

Parameters are estimated by CML.

Examples

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

summary(res_drm)

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.

Author(s)

Christine Hohensinn