Title
Identification of the 1PL Model with Guessing Parameter: Parametric and Semi-parametric Results
Date Issued
01 April 2013
Access level
metadata only access
Resource Type
journal article
Author(s)
San Martín E.
Rolin J.M.
Universidad de Concepción
Publisher(s)
Springer Science and Business Media, LLC
Abstract
In this paper, we study the identification of a particular case of the 3PL model, namely when the discrimination parameters are all constant and equal to 1. We term this model, 1PL-G model. The identification analysis is performed under three different specifications. The first specification considers the abilities as unknown parameters. It is proved that the item parameters and the abilities are identified if a difficulty parameter and a guessing parameter are fixed at zero. The second specification assumes that the abilities are mutually independent and identically distributed according to a distribution known up to the scale parameter. It is shown that the item parameters and the scale parameter are identified if a guessing parameter is fixed at zero. The third specification corresponds to a semi-parametric 1PL-G model, where the distribution G generating the abilities is a parameter of interest. It is not only shown that, after fixing a difficulty parameter and a guessing parameter at zero, the item parameters are identified, but also that under those restrictions the distribution G is not identified. It is finally shown that, after introducing two identification restrictions, either on the distribution G or on the item parameters, the distribution G and the item parameters are identified provided an infinite quantity of items is available. © 2013 The Psychometric Society.
Start page
341
End page
379
Volume
78
Issue
2
Language
English
OCDE Knowledge area
Estadísticas, Probabilidad
Scopus EID
2-s2.0-84875379712
PubMed ID
Source
Psychometrika
ISSN of the container
00333123
Sponsor(s)
The work developed in this paper was presented in a Symposium on Identification Problems in Psychometrics at the International Meeting of the Psychometric Society IMPS 2009. The meeting was held in Cambridge (UK), in July 2009. The first author gratefully acknowledges the partial financial support from the ANILLO Project SOC1107 from the Chilean Gouvern-ment. The third author acknowledges the partial financial support from the Grant FONDECYT 11100076 from Chilean Government. The authors gratefully acknowledge several discussions with Claudio Fernández (Faculty of Mathematics, Pontificia Universidad Católica de Chile) and Paul De Boeck (University of Amsterdam). This paper benefited from the helpful suggestions of three anonymous referees and the associate editor. In particular, one of the questions proposed by a referee led us to correct an error in a conclusion of Theorem 2
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