title: Improving statistical analysis of matched case-control studies.
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.
authors: School of Nursing, Midwifery and Paramedicine (QLD), Australian Catholic University, Also Cardiac Catheter Theatres, The Wesley Hospital, Brisbane, Qld., Australia.
authors: Aaron
authors: A
authors: Conway
authors: John X
authors: JX
authors: Rolley
authors: Paul
authors: P
authors: Fulbrook
authors: Karen
authors: K
authors: Page
authors: David R
authors: DR
authors: Thompson
mesh_terms: D000465:Algorithms; D016022:Case-Control Studies; D035061:Control Groups; D003627:Data Interpretation, Statistical; D003657:Decision Making; D006801:Humans; D015399:Nursing Research / Q000379:methods*; D012107:Research Design