Improving statistical analysis of matched case-control studies

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

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

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
Volume36
Issue number3
DOIs
Publication statusPublished - Jun 2013
Externally publishedYes

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Case-Control Studies
Statistical Data Interpretation
Decision Making
Nursing
Research Design
Power (Psychology)

Cite this

Conway, Aaron ; Rolley, John X. ; Fulbrook, Paul ; Page, Karen ; Thompson, David R. / Improving statistical analysis of matched case-control studies. In: Research in Nursing and Health. 2013 ; Vol. 36, No. 3. pp. 320-324.
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Improving statistical analysis of matched case-control studies. / Conway, Aaron; Rolley, John X.; Fulbrook, Paul; Page, Karen; Thompson, David R.

In: Research in Nursing and Health, Vol. 36, No. 3, 06.2013, p. 320-324.

Research output: Contribution to journalArticle

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