Efficient estimation in multi-phase case-control studies.

LEE, A. J.; SCOTT, A. J.; WILD, C. J.

In this paper we discuss the analysis of multi-phase, or multi-stage, case-control studies and present an efficient semiparametric maximum-likelihood approach that unifies and extends earlier work, including the seminal case-control paper by Prentice & Pyke (1979), work by Breslow & Cain (1988), Scott & Wild (1991), Breslow & Holubkov (1997) and others. The theoretical derivations apply to arbitrary binary regression models but we present results for logistic regression and show that the approach can be implemented by including additional intercept terms in the logistic model and then making some simple corrections to the score and information equations used in a Newton–Raphson or Fisher-scoring maximization of the prospective loglikelihood.

LOGISTIC regression analysis; MAXIMUM likelihood statistics; CASE-control method; RESPONSE surfaces (Statistics); NEWTON-Raphson method

Biometrika, 2010, Vol 97, Issue 2, p361

0006-3444

Academic Journal

10.1093/biomet/asq009