Now showing items 11-20 of 228
Latent variable models for gene–environment interactions in longitudinal studies with multiple correlated exposures
(Chapman & Hall/CRCWiley Periodicals, Inc., 2015-03-30)
Non-parametric estimation of gap time survival functions for ordered multivariate failure time data
(John Wiley & Sons, Ltd., 2004-06-30)
Times between sequentially ordered events (gap times) are often of interest in biomedical studies. For example, in a cancer study, the gap times from incidence-to-remission and remission-to-recurrence may be examined. Such ...
A shared random effects model for censored medical costs and mortality
(John Wiley & Sons, Ltd., 2006)
In this paper, we propose a model for medical costs recorded at regular time intervals, e.g. every month, as repeated measures in the presence of a terminating event, such as death. Prior models have related monthly medical ...
Semiparametric inferences for association with semi-competing risks data
(John Wiley & Sons, Ltd., 2005)
In many biomedical studies, it is of interest to assess dependence between bivariate failure time data. We focus here on a special type of such data, referred to as semi-competing risks data. In this article, we develop ...
The synthesis and chemistry of certain anthelmintic benzimidazoles
(Elsevier, 1990-04)
A basis for interest in the benzimidazole ring system as a nucleus from which to develop potential chemotherapeutic agents was established in the 1950s when it was found that 5,6-dimethyl-l-([alpha]-D-ribofuranosyl)benzimidazole ...
Methods for comparing center‐specific survival outcomes using direct standardization
(Wiley, 2014-05-30)
The evaluation of center‐specific outcomes is often through survival analysis methods. Such evaluations must account for differences in the distribution of patient characteristics across centers. In the context of censored ...
Multiple imputation of missing covariates for the Cox proportional hazards cure model
(John Wiley and Sons, Inc, 2016-11-20)
Analysis on binary responses with ordered covariates and missing data
(John Wiley & Sons, Ltd., 2007-08-15)
We consider the situation of two ordered categorical variables and a binary outcome variable, where one or both of the categorical variables may have missing values. The goal is to estimate the probability of response of ...