Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies

The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to…

• NI
  National Institutes of Health

  Awards: UL1 TR000371, TR000371
• CF
  Center for Clinical and Translational Sciences, University of Texas Health Science Center at Houston

  Awards: UL1 TR000371, TR000371
• NC
  National Center for Advancing Translational Sciences

  Awards: UL1 TR000371, TR000371