Selecting Controls for Assessing Interaction in Nested Case-control Studies

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概要

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• Background: Two methods for selecting controls in nested case-control studies - matching on Xand counter matching on X - are compared when interest is in interaction between a risk factor X measured in the full cohort and another risk factor Z measured only in the case-control sample. This is important because matching provides efficiency gains relative to random sampling when X is uncommon and the interaction is positive (greater than multiplicative), whereas counter matching is generally efficient compared to random sampling.Methods: Matching and counter matching were compared to each other and to random sampling of controls for dichotomous X and Z Comparison was by simulation, using as an example a published study of radiation and other risk factors for breast cancer in the Japanese atomic-bomb survivors, and by asymptotic relative efficiency calculations for a wide range of parameters specifying the prevalence of X and Z as well as the levels of correlation and interaction between them. Focus was on analyses utilizing general models for the joint risk of X and Z.Results: Counter-matching performed better than matching or random sampling in terms of efficiency for inference about interaction in the case of a rare risk factor X and uncorrelated risk factor Z. Further, more general, efficiency calculations demonstrated that counter-matching is generally efficient relative to matched case-control designs for studying interaction.Conclusions: Because counter-matched designs may be analyzed using standard statistical methods and allow investigation of confounding of the effect of X, whereas matched designs require a non-stan- dard approach when fitting general risk models and do not allow investigating the adjusted risk of X, it is concluded that counter-matching on X can be a superior alternative to matching on X in nested case- control studies of interaction when X is known at the time of case-control sampling.J Epidemiol 2003;13:193-202.

• 日本疫学会の論文
• 2003-07-01

著者

• COLOGNE John

  Department of Statistics, Radiation Effects Research Foundation

• Cologne John

  Department Of Statistics Radiation Effects Research Foundation

• LANGHOLZ Bryan

  Division of Biostatistics, Department of Preventive Medicine, University of Southern California Keck

• Langholz Bryan

  Division Of Biostatistics Department Of Preventive Medicine University Of Southern California Keck S

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• Selecting Controls for Assessing Interaction in Nested Case-control Studies
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