The Effect of Bias on Estimators of Relative Risk for Pair-Matched and Stratified Samples
作者:
SonjaM. McKinlay,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1975)
卷期:
Volume 70,
issue 352
页码: 859-864
ISSN:0162-1459
年代: 1975
DOI:10.1080/01621459.1975.10480314
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
Monte Carlo methods are employed to compare the effectiveness of pair-matched and independent stratified samples for estimating relative risk in the presence of bias. Three approximations to the maximum likelihood estimator for stratified samples suggested by Woolf, Mantel and Haenszel and Birch, respectively [25, 17, 2], are also compared. The sampling model is modified to approximate the practical choices for a researcher and to allow for the loss of unmatchable sample units. The mean square error is always largest for the matched-pairs estimator, while of the stratified estimators, Woolf's consistently produces the smallest MSE, equaled only by Birch's when the samples are equal.
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