Tags

Type your tag names separated by a space and hit enter

The Rasch model, additive conjoint measurement, and new models of probabilistic measurement theory.
J Appl Meas. 2001; 2(4):389-423.JA

Abstract

This research describes some of the similarities and differences between additive conjoint measurement (a type of fundamental measurement) and the Rasch model. It seems that there are many similarities between the two frameworks, however, their differences are nontrivial. For instance, while conjoint measurement specifies measurement scales using a data-free, non-numerical axiomatic frame of reference, the Rasch model specifies measurement scales using a numerical frame of reference that is, by definition, data dependent. In order to circumvent difficulties that can be realistically imposed by this data dependence, this research formalizes new non-parametric item response models. These models are probabilistic measurement theory models in the sense that they explicitly integrate the axiomatic ideas of measurement theory with the statistical ideas of order-restricted inference and Markov Chain Monte Carlo. The specifications of these models are rather flexible, as they can represent any one of several models used in psychometrics, such as Mokken's (1971) monotone homogeneity model, Scheiblechner's (1995) isotonic ordinal probabilistic model, or the Rasch (1960) model. The proposed non-parametric item response models are applied to analyze both real and simulated data sets.

Authors+Show Affiliations

LSU Health Sciences Center, New Orleans, LA 70112-1393, USA. gkarab@lsuhsc.edu

Pub Type(s)

Comparative Study
Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

12011506

Citation

Karabatsos, G. "The Rasch Model, Additive Conjoint Measurement, and New Models of Probabilistic Measurement Theory." Journal of Applied Measurement, vol. 2, no. 4, 2001, pp. 389-423.
Karabatsos G. The Rasch model, additive conjoint measurement, and new models of probabilistic measurement theory. J Appl Meas. 2001;2(4):389-423.
Karabatsos, G. (2001). The Rasch model, additive conjoint measurement, and new models of probabilistic measurement theory. Journal of Applied Measurement, 2(4), 389-423.
Karabatsos G. The Rasch Model, Additive Conjoint Measurement, and New Models of Probabilistic Measurement Theory. J Appl Meas. 2001;2(4):389-423. PubMed PMID: 12011506.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - The Rasch model, additive conjoint measurement, and new models of probabilistic measurement theory. A1 - Karabatsos,G, PY - 2002/5/16/pubmed PY - 2002/6/20/medline PY - 2002/5/16/entrez SP - 389 EP - 423 JF - Journal of applied measurement JO - J Appl Meas VL - 2 IS - 4 N2 - This research describes some of the similarities and differences between additive conjoint measurement (a type of fundamental measurement) and the Rasch model. It seems that there are many similarities between the two frameworks, however, their differences are nontrivial. For instance, while conjoint measurement specifies measurement scales using a data-free, non-numerical axiomatic frame of reference, the Rasch model specifies measurement scales using a numerical frame of reference that is, by definition, data dependent. In order to circumvent difficulties that can be realistically imposed by this data dependence, this research formalizes new non-parametric item response models. These models are probabilistic measurement theory models in the sense that they explicitly integrate the axiomatic ideas of measurement theory with the statistical ideas of order-restricted inference and Markov Chain Monte Carlo. The specifications of these models are rather flexible, as they can represent any one of several models used in psychometrics, such as Mokken's (1971) monotone homogeneity model, Scheiblechner's (1995) isotonic ordinal probabilistic model, or the Rasch (1960) model. The proposed non-parametric item response models are applied to analyze both real and simulated data sets. SN - 1529-7713 UR - https://www.unboundmedicine.com/medline/citation/12011506/The_Rasch_model_additive_conjoint_measurement_and_new_models_of_probabilistic_measurement_theory_ DB - PRIME DP - Unbound Medicine ER -