Case-control analysis with a continuous outcome variable

Stat Med. 2009 Jan 30;28(2):194-204. doi: 10.1002/sim.3474.

Abstract

It is not uncommon for a continuous outcome variable Y to be dichotomized and analysed using logistic regression. Moser and Coombs (Statist. Med. 2004; 23:1843-1860) provide a method for converting the output from a standard linear regression analysis using the original continuous outcome Y to give much more efficient inferences about the same odds-ratio parameters being estimated by the logistic regression. However, these results apply only to prospective studies. This paper follows up Moser and Coombs by providing an efficient linear-model-based solution for data collected using case-control studies. Gains in statistical efficiency of up to 240 per cent are obtained even with small to moderate odds ratios. Differences in design efficiency between case-control and prospective sampling designs are found to be much smaller, however, when linear-model-based analyses are being used than they are when logistic regression analyses are being used.

MeSH terms

  • Case-Control Studies*
  • Confidence Intervals
  • Humans
  • Linear Models
  • Odds Ratio
  • Outcome Assessment, Health Care / statistics & numerical data*