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Estimation of the Parameters in an Item-Cloning Model for Adaptive Testing

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Elements of Adaptive Testing

Part of the book series: Statistics for Social and Behavioral Sciences ((SSBS))

Abstract

Item response theory (IRT) models with random person parameters have become a common choice among practitioners in the field of educational and psychological measurement. Though initially the choice for such models was motivated by an attempt to get rid of the statistical problems inherent in the incidental nature of the person parameters (Bock & Lieberman, 1970), the insight soon emerged that such models more adequately represent cases where the focus is not on the measurement of individual persons but on the estimation of characteristics of populations. Early examples of models with random person parameters in the literature are those proposed by Andersen and Madsen (1977) and Sanathanan and Blumenthal (1978), who were interested in estimates of the mean and variance in a population of persons, and by Mislevy (1991), who provided tools for inference from a response model with a regression structure on the person parameters introduced to account for sampling persons differing background variables.

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Author information

Authors and Affiliations

  1. Department of Research Methodology, Measurement, and Data Analysis, University of Twente, 217, 7500, AE, Enschede, The Netherlands

    Cees A. W. Glas & Hanneke Geerlings

  2. CTB/McGraw-Hill, 20 Ryan Ranch Road, Monterey, CA, 93940, USA

    Wim J. van der Linden

Authors
  1. Cees A. W. Glas
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  2. Wim J. van der Linden
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  3. Hanneke Geerlings
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Editors and Affiliations

  1. CTB/McGraw-Hill LLC, Ryan Ranch Road 20, Monterey, 93940, U.S.A.

    Wim J. van der Linden

  2. Fac. Behavioural Sciences, Twente University, Enschede, Netherlands

    Cees A.W. Glas

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Glas, C.A.W., van der Linden, W.J., Geerlings, H. (2009). Estimation of the Parameters in an Item-Cloning Model for Adaptive Testing. In: van der Linden, W., Glas, C. (eds) Elements of Adaptive Testing. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-0-387-85461-8_15

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