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Analysis of matched case-control studies
by
Pearce, Neil
in
Age groups
/ Case-Control Studies
/ Confounding Factors (Epidemiology)
/ Control Groups
/ Data Interpretation, Statistical
/ Lung cancer
/ Methods
/ Regression analysis
/ Research Methods & Reporting
/ Scandals
2016
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Do you wish to request the book?
Analysis of matched case-control studies
by
Pearce, Neil
in
Age groups
/ Case-Control Studies
/ Confounding Factors (Epidemiology)
/ Control Groups
/ Data Interpretation, Statistical
/ Lung cancer
/ Methods
/ Regression analysis
/ Research Methods & Reporting
/ Scandals
2016
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Journal Article
Analysis of matched case-control studies
2016
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Overview
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.
Publisher
BMJ Publishing Group LTD,BMJ Publishing Group Ltd
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