title: Case-control analysis with a continuous outcome variable.
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.
authors.affiliation: Department of Statistics, The University of Auckland, Private Bag 92019, Auckland, New Zealand.
authors.forename: Yannan
authors.initials: Y
authors.lastname: Jiang
authors.forename: Alastair
authors.initials: A
authors.lastname: Scott
authors.forename: Chris J
authors.initials: CJ
authors.lastname: Wild
mesh_terms: D016022:Case-Control Studies; D016001:Confidence Intervals; D006801:Humans; D016014:Linear Models; D016017:Odds Ratio; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*