An evaluation of marginal maximum likelihood estimation for the two-parameter logistic model

Loading...
Thumbnail Image

View/Download File

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

An evaluation of marginal maximum likelihood estimation for the two-parameter logistic model

Published Date

1989

Publisher

Type

Article

Abstract

The accuracy of marginal maximum likelihood estimates of the item parameters of the two-parameter logistic model was investigated. Estimates were obtained for four sample sizes and four test lengths; joint maximum likelihood estimates were also computed for the two longer test lengths. Each condition was replicated 10 times, which allowed evaluation of the accuracy of estimated item characteristic curves, item parameter estimates, and estimated standard errors of item parameter estimates for individual items. Items that are typical of a widely used job satisfaction scale and moderately easy tests had satisfactory marginal estimates for all sample sizes and test lengths. Larger samples were required for items with extreme difficulty or discrimination parameters. Marginal estimation was substantially better than joint maximum likelihood estimation. Index terms: Fletcher-Powell algorithm, item parameter estimation, item response theory, joint maximum likelihood estimation, marginal maximum likelihood estimation, two-parameter logistic model.

Keywords

Description

Related to

Replaces

License

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Drasgow, Fritz. (1989). An evaluation of marginal maximum likelihood estimation for the two-parameter logistic model. Applied Psychological Measurement, 13, 77-90. doi:10.1177/014662168901300108

Suggested citation

Drasgow, Fritz. (1989). An evaluation of marginal maximum likelihood estimation for the two-parameter logistic model. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/107037.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.