Median Unbiased Estimation for Binary Data
作者:
KarimF. Hirji,
AnastasiosA. Tsiatis,
CyrusR. Mehta,
期刊:
The American Statistician
(Taylor Available online 1989)
卷期:
Volume 43,
issue 1
页码: 7-11
ISSN:0003-1305
年代: 1989
DOI:10.1080/00031305.1989.10475597
出版商: Taylor & Francis Group
关键词: Accuracy of an estimator;Maximum likelihood estimator;Sufficient statistic
数据来源: Taylor
摘要:
This article compares the accuracy of the median unbiased estimator with that of the maximum likelihood estimator for a logistic regression model with two binary covariates. The former estimator is shown to be uniformly more accurate than the latter for small to moderately large sample sizes and a broad range of parameter values. In view of the recently developed efficient algorithms for generating exact distributions of sufficient statistics in binary-data problems, these results call for a serious consideration of median unbiased estimation as an alternative to maximum likelihood estimation, especially when the sample size is not large, or when the data structure is sparse.
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