Resumen de Improving statistical analysis of matched case�control studies
Aaron Conway, John X. Rolley, Paul Fulbrook, Karen Page, David R. Thompson
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.
