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We read with interest Neil Pearce’s recent commentary on matching in case-control studies (1). We concur with Dr. Pearce that the benefits and costs of matching in a case-control design are not widely recognized and that worked examples can help to provide the intuition necessary to make smart study design choices.
For students and researchers interested in exploring issues regarding matching more deeply, we recently developed the Match-o-matic, a freely available web-based study design simulator. Match-o-matic users can specify matching parameters for case-control studies nested within a larger cohort and compare the odds ratios and confidence intervals resulting from these selections. Users can then explore precision gains, precision losses, and biases that result from not only from too wide or too narrow matching tolerances, but also from the choice to match at all.
Because nested case-control studies are often used in molecular epidemiology, the Match-o-matic also explores the logistical constraints that matching places upon lab analyses for such studies. For lab assays that suffer from batch and/or storage duration effects, biological samples from matched case-control pairs should be analyzed in the same analytical batch (2,3). The set of samples that need to be analyzed together grows when stringent matching criteria require individuals to serve as controls for multiple cases or when individuals selected to be controls subsequently become cases (2). The Match-o-matic displays a network map highlighting the groups of linked cases and controls whose biological samples need to processed in a single analytical batch.
We encourage researchers and students to use the Match-o-matic, available at http://episimulations.net, to explore the trade-offs involved in designing matched case-control studies.
The authors declare no competing interests.
1. Pearce, N. Analysis of matched case-control studies. bmj 352, i969 (2016).
2. Rundle, A.G., Vineis, P. & Ahsan, H. Design options for molecular epidemiology research within cohort studies. Cancer Epidemiology Biomarkers & Prevention 14, 1899-1907 (2005).
3. Wild, C., Vineis, P. & Garte, S. Molecular epidemiology of chronic diseases, (John Wiley & Sons, 2011).
Competing interests:
No competing interests
08 March 2016
Andrew Ratanatharathorn
PhD Student
Stephen J Mooney, Andrew G Rundle
Department of Epidemiology, Mailman School of Public Health, Columbia University in the City of New York
Response to Neil Pearce’s Analysis of Matched Case-Control Studies
We read with interest Neil Pearce’s recent commentary on matching in case-control studies (1). We concur with Dr. Pearce that the benefits and costs of matching in a case-control design are not widely recognized and that worked examples can help to provide the intuition necessary to make smart study design choices.
For students and researchers interested in exploring issues regarding matching more deeply, we recently developed the Match-o-matic, a freely available web-based study design simulator. Match-o-matic users can specify matching parameters for case-control studies nested within a larger cohort and compare the odds ratios and confidence intervals resulting from these selections. Users can then explore precision gains, precision losses, and biases that result from not only from too wide or too narrow matching tolerances, but also from the choice to match at all.
Because nested case-control studies are often used in molecular epidemiology, the Match-o-matic also explores the logistical constraints that matching places upon lab analyses for such studies. For lab assays that suffer from batch and/or storage duration effects, biological samples from matched case-control pairs should be analyzed in the same analytical batch (2,3). The set of samples that need to be analyzed together grows when stringent matching criteria require individuals to serve as controls for multiple cases or when individuals selected to be controls subsequently become cases (2). The Match-o-matic displays a network map highlighting the groups of linked cases and controls whose biological samples need to processed in a single analytical batch.
We encourage researchers and students to use the Match-o-matic, available at http://episimulations.net, to explore the trade-offs involved in designing matched case-control studies.
The authors declare no competing interests.
1. Pearce, N. Analysis of matched case-control studies. bmj 352, i969 (2016).
2. Rundle, A.G., Vineis, P. & Ahsan, H. Design options for molecular epidemiology research within cohort studies. Cancer Epidemiology Biomarkers & Prevention 14, 1899-1907 (2005).
3. Wild, C., Vineis, P. & Garte, S. Molecular epidemiology of chronic diseases, (John Wiley & Sons, 2011).
Competing interests: No competing interests