Quasi score equations derived from corrected mean and variance functions allow for consistent parameter estimation under measure ment error However the practical use of some approaches relying on this general methodological principle was strongly limited by the assumptions underlying them only one covariate was allowed to be measured with non negligible error and additionally this covariate had...

Graphical methods based on the analysis of differences between log cumulative hazard functions are considered for a two-group semi-proportional hazard model which allows for interaction between treatments and covariates. Confidence procedures and test statistics that can be used to test for interaction and for main effects are developed. Their use is illustrated by applying them to the analysis...

Exposure measurement error represents one of the most important sources of uncertainty in epidemiology. When exposure uncertainty is not or only poorly accounted for, it can lead to biased risk estimates and a distortion of the shape of the exposure-response relationship. In occupational cohort studies, the time-dependent nature of exposure and changes in the method of exposure assessment may c...

We extend the proportional hazards model to a two-level model with a random intercept term and random coefficients. The parameters in the multilevel model are estimated by a combination of EM and Newton-Raphson algorithms. Even for samples of 50 groups, this method produces estimators of the fixed effects coefficients that are approximately unbiased and normally distributed. Two different metho...

Studies in the health sciences often give rise to correlated survival data. Wei, Lin, and Weissfeld (1989, Journal of the American Statistical Association 84, 1065-1073) and Lee, Wei, and Amato (1992, in Survival Analysis: State of the Art) showed that, if the marginal distributions of the correlated survival times follow a proportional hazards model, then the estimates from Cox's partial likel...