title: Two-phase outcome-dependent studies for failure times and testing for effects of expensive covariates.
abstract: Two- or multi-phase study designs are often used in settings involving failure times. In most studies, whether or not certain covariates are measured on an individual depends on their failure time and status. For example, when failures are rare, case-cohort or case-control designs are used to increase the number of failures relative to a random sample of the same size. Another scenario is where certain covariates are expensive to measure, so they are obtained only for selected individuals in a cohort. This paper considers such situations and focuses on cases where we wish to test hypotheses of no association between failure time and expensive covariates. Efficient score tests based on maximum likelihood are developed and shown to have a simple form for a wide class of models and sampling designs. Some numerical comparisons of study designs are presented.
authors.affiliation: Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada. jlawless@uwaterloo.ca.
authors.forename: J F
authors.initials: JF
authors.lastname: Lawless
mesh_terms: D015982:Bias; D015331:Cohort Studies; D003198:Computer Simulation; D056726:Genetic Association Studies; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D016016:Proportional Hazards Models
keywords: Cohort sampling designs; Generalized linear transformation models; Genetic association tests; Missing data