Pearce, Neil; (2016) Analysis of matched case-control studies. BMJ (Clinical research ed), 352. i969-. ISSN 0959-8138 DOI: https://doi.org/10.1136/bmj.i969
Permanent Identifier
Use this Digital Object Identifier when citing or linking to this resource.
Abstract
There are two common misconceptions about case-control studies: that matching in itself eliminates (controls) confounding by the matching factors, and that if matching has been performed, then a “matched analysis” is required. However, matching in a case-control study does not control for confounding by the matching factors; in fact it can introduce confounding by the matching factors even when it did not exist in the source population. Thus, a matched design may require controlling for the matching factors in the analysis. However, it is not the case that a matched design requires a matched analysis. Provided that there are no problems of sparse data, control for the matching factors can be obtained, with no loss of validity and a possible increase in precision, using a “standard” (unconditional) analysis, and a “matched” (conditional) analysis may not be required or appropriate.
Item Type | Article |
---|---|
Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Medical Statistics |
Research Centre | ?? 208138 ?? |
PubMed ID | 26916049 |
ISI | 371116400004 |
Related URLs |
Downloads
Filename: matched analysis bmj.pdf
Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 3.0
Download