Controlling Bias in Observational Studies: A Review
Cambridge University Press eBooksPublished 4 September 2006
William G. Cochran
Citations986
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
Work on the effectiveness of different methods of matched sampling and statistical adjustment, alone and in combination, in reducing bias due to confounding x-variables when comparing two populations is reviewed.
Abstract
A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Keywords
Mathematics
Wiley series in probability and statisticsLinear Statistical Inference and its Applications
10,509 Citations1973C. Radhakrishna Rao
Cambridge University Press eBooksMatching to Remove Bias in Observational Studies
614 Citations2006Donald B. Rubin
Cambridge University Press eBooksThe Use of Matched Sampling and Regression Adjustment to Remove Bias in Observational Studies
457 Citations2006Donald B. Rubin
Journal of the Royal Statistical Society Series C (Applied Statistics)A Dictionary of Statistical Terms.
256 Citations1957P. D. Oldham, M. G. Kendall +1 more
Journal of the Royal Statistical Society Series C (Applied Statistics)A Technique for Studying the Effects of a Television Broadcast
83 Citations1956William A. Belson
American Journal of SociologyThe Computerized Construction of a Matched Sample
79 Citations1970Robert P. Althauser, Donald B. Rubin
The quality of matches is found to be fairly high and attrition has been virtually elliminated, thus demonstrating the possibilities of the three approaches to the computerization of matching.
The Journal of Educational ResearchA Method of Matching Groups for Experiment with No Loss of Population
68 Citations1941Charles C. Peters
