Salzberger, Thomas. 2015. The validity of polytomous items in the Rasch model - The role of statistical evidence of the threshold order. Psychological Test and Assessment Modeling. 57 (3), 377-395.

RIS

@ARTICLE{Salzberger2015,
title = {The validity of polytomous items in the Rasch model - The role of statistical evidence of the threshold order},
author = {Thomas Salzberger},
year = {2015},
doi = {n.a.},
url = {http://www.psychologie-aktuell.com/fileadmin/download/ptam/3-2015_20150925/05_Salzberger.pdf},
volume = {57},
number = {3},
language = {EN},
pages = {377-395},
journal = {Psychological Test and Assessment Modeling},
abstract = {Rating scales involving more than two response categories are a popular response format in measurement in education, health and business sciences. Their primary purpose lies in the increase of information and thus measurement precision. For these objectives to be met, the response scale has to provide valid scores with higher numbers reflecting more of the property to be measured. Thus, the response scale is closely linked to construct validity since any kind of malfunctioning would jeopardize measurement. While tests of fit are not necessarily sensitive to violations of the assumed order of response categories, the order of empirical threshold estimates provides insight into the functionality of the scale. The Rasch model and, specifically, the so-called Rasch-Andrich thresholds are unique in providing this kind of evidence. The conclusion whether thresholds are to be considered truly ordered or disordered can be based on empirical point estimates of thresholds. Alternatively, statistical tests can be carried out taking standard errors of threshold estimates into account. Such tests might either stress the need for evidence of ordered thresholds or the need for a lack of evidence of disordered thresholds. Both approaches are associated with unacceptably high error rates, though. A hybrid approach that accounts for both evidence of ordered and disordered thresholds is suggested as a compromise. While the usefulness of statistical tests for a given data set is still limited, they provide some guidance in terms of a modified response scale in future applications.},
}