Improving statistical analysis of matched case�control studies

• Autores: Aaron Conway, John X. Rolley, Paul Fulbrook, Karen Page, David R. Thompson
• Localización: Research in nursing and health, ISSN-e 1098-240X, Vol. 36, Nº. 3, 2013, págs. 320-324
• Idioma: inglés
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• Resumen

  • 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.