Improving statistical analysis of matched case–control studies. Issue 3 (13th February 2013)

• Record Type: Journal Article
• Authors: Conway, Aaron; Rolley, John X.; Fulbrook, Paul; Page, Karen; Thompson, David R.
• Is Part Of: Research in nursing & health. Volume 36:Issue 3(2013:Jun.)
• Page Start: 320
• Page End: 324
• Publication Date: 2013-02-13
• Subjects: Nursing -- Research -- Periodicals; Nursing -- Periodicals; 610.7305
• DOI: 10.1002/nur.21536
• Languages: English
• ISSNs: 0160-6891

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>Abstract</title> <p>Matched case–control research designs can be useful because matching can increase power due to reduced variability between subjects. However, inappropriate statistical analysis of matched data could result in a change in the strength of association between the dependent and independent variables or a change in the significance of the findings. We sought to ascertain whether matched case–control studies published in the nursing literature utilized appropriate statistical analyses. Of 41 articles identified that met the inclusion criteria, 31 (76%) used an inappropriate statistical test for comparing data derived from case subjects and their matched controls. In response to this finding, we developed an algorithm to support decision‐making regarding statistical tests for matched case–control studies. © 2013 Wiley Periodicals, Inc. Res Nurs Health 36:320–324, 2013</p> </abstract>