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Four Bootstrap Confidence Intervals for the Binomial-Error Model

Published online by Cambridge University Press:  01 January 2025

Miao-Hsiang Lin*
Affiliation:
Institute of Statistical Science, Academia Sinica
Chao A. Hsiung
Affiliation:
Institute of Statistical Science, Academia Sinica
*
Requests for reprints should be sent to Miao-Hsiang Lin, Institute of Statistical Science, Academia Sinica, Taipei, 11529, Taiwan, R.O.C.

Abstract

Confidence intervals for the mean function of the true proportion score (μζ|x), where ζ and x respectively denote the true proportion and observed test scores, can be approximated by the Efron, Bayesian, and parametric empirical Bayes (PEB) bootstrap procedures. The similarity of results yielded by all the bootstrap methods suggests the following: the unidentifiability problem of the prior distribution g(ζ) can be bypassed with respect to the construction of confidence intervals for the mean function, and a beta distribution for g(ζ) is a reasonable assumption for the test scores in compliance with a negative hypergeometric distribution. The PEB bootstrap, which reflects the construction of Morris intervals, is introduced for computing predictive confidence bands for ζ|x. It is noted that the effect of test reliability on the precision of interval estimates varies with the two types of confidence statements concerned.

Type
Original Paper
Copyright
Copyright © 1992 The Psychometric Society

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Footnotes

The Authors are indebted to the Editor and anonymous reviewers for constructive suggestions and comments. The authors wish to thank Min-Te Chao and Cheng-Der Fuh for some useful suggestions at earlier stages of writing this paper.

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