Improving statistical analysis of matched case-control studies

Aaron Conway, John X. Rolley, Paul Fulbrook, Karen Page, David R. Thompson

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)320-324
Number of pages5
JournalResearch in Nursing and Health
Issue number3
Publication statusPublished - Jun 2013
Externally publishedYes


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