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Item Parameter Estimation Via Marginal Maximum Likelihood and an EM Algorithm: A Didactic

Michigan State University

Frank B. Baker

University of Wisconsin-Madison

Michael Zwarts

National Institute for Educational Measurement, The Netherlands

The Bock and Aitkin (1981) Marginal Maximum Likelihood/EM approach to item parameter estimation is an alternative to the classical joint maximum likelihood procedure of item response theory. Unfortunately_, the complexity of the underlying mathematics and the terse nature of the existing literature has made understanding of the approach difficult. To make the approach accessible to a wider audience, the present didactic paper provides the essential mathematical details of a marginal maximum likelihood/EM solution and shows how it can be used to obtain consistent item parameter estimates. For pedagogical purposes, a short BASIC computer program is used to illustrate the underlying simplicity of the method.

Journal of Educational and Behavioral Statistics, Vol. 13, No. 3, 243-271 (1988)
DOI: 10.3102/10769986013003243


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