%0 Journal Article
%T Rasch and pseudo-Rasch models: suitableness for practical test applications
%A HARTMANN H. SCHEIBLECHNER
%J Psychology Science Quarterly
%D 2009
%I 
%X The Rasch model has been suggested for psychological test data (subjects items) for various scales of measurement. It is defined to be specifically objective. If the data are dichotomous, the use of the dichotomous model of Rasch for psychological test construction is almost inevitable. The two- and three-parameter logistic models of Birnbaum and further models with additional parameters are not always identifiable. The linear logistic model is useful for the construction of item pools. For polytomous graded response data, there are useful models (Samejima, 1969; Tutz, 1990; and again by Rasch, cf. Fischer, 1974, or Kubinger, 1989) which, however, are not specifically objective. The partial credit model (Masters, 1982) is not meaningful in a measurement theory sense. For polytomous nominal data, the multicategorical Rasch model is much too rarely applied. There are limited possibilities for locally dependent data. The mixed Rasch model is not a true Rasch model, but useful for model controls and heuristic purposes. The models for frequency data and continuous data are not discussed here. The nonparametric ISOP-models are "sample independent" (ordinally specifically objective) models for (up to 3 dependent) graded responses providing ordinal scales or interval scales for subject-, item- and response-scale-parameters. The true achievement of sample-independent Rasch models is an extraordinary generalizeability of psychological assessment procedures.
%K specific objectivity
%K measurement structures
%K graded responses
%K local dependence
%K generalized assessment procedures
%U http://www.psychologie-aktuell.com/fileadmin/download/PschologyScience/2-2009/05_Scheiblechner.pdf