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Estimating the Polyserial Correlation Coefficient

Published online by Cambridge University Press:  01 January 2025

Edward J. Bedrick  and
Frederick C. Breslin
Edward J. Bedrick*
Affiliation:
Department of Mathematics and Statistics, University of New Mexico
Frederick C. Breslin
Affiliation:
Science Applications International Corporation
*
Requests for reprints should be sent to Edward J. Bedrick, Dept. of Mathematics and Statistics, University of New Mexico, Albuquerque, NM 87131. Electronic mail requests should be sent to bedrick@math.unm.edu.
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Abstract

We develop simple noniterative estimators of the polyserial correlation coefficient. A general relationship between the polyserial correlation and the point polyserial correlation is exploited to give extensions of Pearson's, Brogden's, and Lord's biserial estimators to the multicategory setting. The small sample and asymptotic properties of these estimators are studied in some detail. A comparison with maximum likelihood estimates shows that Lord's polyserial estimator is fairly efficient across three probability models.

Keywords

biserial correlationBrogden's estimatorLord's estimatormaximum likelihood
Type
Original Paper
Information
Psychometrika , Volume 61 , Issue 3 , September 1996 , pp. 427 - 443
Copyright
Copyright © 1996 The Psychometric Society

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Footnotes

The authors would like to thank the referees for suggestions that improved the presentation of the paper.

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