Literature DB >> 7148808

In defense of matching.

J M Karon, L L Kupper.   

Abstract

This paper discusses the simplified situation of an epidemiologic study involving disease, exposure, and a single (possibly confounding) extraneous factor, all of which are dichotomous. The question is: In studying the association between disease and exposure, should the comparison group be selected by random sampling or by matching on the extraneous factor? An example is used to demonstrate the general principle that matching controls confounding in estimating the risk ratio in a follow-up study, but not in estimating the exposure odds ratio in a case-control study. Calculations based on a probability model show that, despite the possible reduction in sample size which may be associated with matching, matching will often lead to a more precise estimate of the effect measure than random sampling and is not likely to result in a significant loss in precision in situations of practical importance. Therefore, selection of the referent group by matching should be given serious consideration for both follow-up and case-control studies.

Mesh:

Year:  1982        PMID: 7148808     DOI: 10.1093/oxfordjournals.aje.a113476

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  4 in total

1.  An empirical investigation on matching in published case-control studies.

Authors:  O Gefeller; A Pfahlberg; H Brenner; J Windeler
Journal:  Eur J Epidemiol       Date:  1998-06       Impact factor: 8.082

2.  Economic burden of renal cell carcinoma in the US: Part II--an updated analysis.

Authors:  Ya-Chen T Shih; Chun-Ru Chien; Ying Xu; I-Wen Pan; Grace L Smith; Thomas A Buchholz
Journal:  Pharmacoeconomics       Date:  2011-04       Impact factor: 4.981

3.  Maternal smoking during pregnancy and children's cognitive and physical development: a causal risk factor?

Authors:  Stephen E Gilman; Hannah Gardener; Stephen L Buka
Journal:  Am J Epidemiol       Date:  2008-07-24       Impact factor: 4.897

4.  The importance of distinguishing between the odds ratio and the incidence rate ratio in GWAS.

Authors:  Berit Lindum Waltoft; Carsten Bøcker Pedersen; Mette Nyegaard; Asger Hobolth
Journal:  BMC Med Genet       Date:  2015-08-30       Impact factor: 2.103

  4 in total

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