You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Estimation for the Rasch Model When Both Ability and Difficulty Parameters Are Random
Steven E. Rigdon and Robert K. Tsutakawa
Journal of Educational Statistics
Vol. 12, No. 1 (Spring, 1987), pp. 76-86
Stable URL: http://www.jstor.org/stable/1164629
Page Count: 11
You can always find the topics here!Topics: Statistical estimation, Estimation methods, Gaussian distributions, Maximum likelihood estimation, Statistical models, Simulations, Datasets, Parametric models, Multilevel models, Point estimators
Were these topics helpful?See something inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
Estimation of the parameters of the Rasch model, a one-parameter item response model, is considered when both the item parameters and the ability parameters are considered random quantities. It is assumed that the item parameters are drawn from a N (γ, τ 2) distribution, and the abilities are drawn from a N(0, σ 2) distribution. A variation of the EM algorithm is used to find approximate maximum likelihood estimates of γ, τ, and σ. A second approach assumes that the difficulty parameters are drawn from a uniform distribution over part of the real line. Real and simulated data sets are discussed for illustration.
Journal of Educational Statistics © 1987 American Educational Research Association