
Accession Number : AD0727212
Title : The Use of Matched Sampling and Regression Adjustment to Remove Bias in Observational Studies.
Descriptive Note : Technical rept.,
Corporate Author : HARVARD UNIV CAMBRIDGE MASS DEPT OF STATISTICS
Personal Author(s) : Rubin,Donald B.
Report Date : 25 JUN 1971
Pagination or Media Count : 52
Abstract : The ability of matched sampling and linear regression adjustment to reduce the bias of an estimate of the treatment effect in two sample observational studies is investigated for a simple matching method and five simple estimates. Monte Carlo results are given for moderately linear exponential response surfaces and analytic results are presented for quadratic response surfaces. The conclusions are (1) in general both matched sampling and regression adjustment can be expected to reduce bias, (2) in some cases when the variance of the matching variable differs in the two populations both matching and regression adjustment can increase bias, (3) when the variance of the matching variable is the same in the two populations and the distributions of the matching variable are symmetric the usual covariance adjusted estimate based on random samples is almost unbiased, and (4) the combination of regression adjustment in matched samples generally produces the least biased estimate. (Author)
Descriptors : (*STATISTICAL ANALYSIS, EXPERIMENTAL DESIGN), REGRESSION ANALYSIS, MONTE CARLO METHOD, COMBINATORIAL ANALYSIS, MATHEMATICAL PREDICTION, SAMPLING
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE