Now showing items 1-6 of 6
Multiple imputation for the analysis of incomplete compound variables
In many settings interest lies in modelling a compound variable defined as a function of two or more component variables. When one or more of the components are missing, the compound variable is not observed and a strategy ...
Does Cox analysis of a randomized survival study yield a causal treatment effect?
(Springer US, 2015-10)
Statistical methods for survival analysis play a central role in the assessment of treatment effects in randomized clinical trials in cardiovascular disease, cancer, and many other fields. The most common approach to ...
Penalized Regression for Interval-Censored Times of Disease Progression: Selection of HLA Markers in Psoriatic Arthritis
Times of disease progression are interval-censored when progression status is only known at a series of assessment times. This situation arises routinely in clinical trials and cohort studies when events of interest are ...
Sample size and robust marginal methods for cluster-randomized trials with censored event times
In cluster-randomized trials, intervention effects are often formulated by specifying marginal models, fitting them under a working independence assumption, and using robust variance estimates to address the association ...
A Cox-Aalen model for interval-censored data
The Cox-Aalen model, obtained by replacing the baseline hazard function in the well-known Cox model with a covariate-dependent Aalen model, allows for both fixed and dynamic covariate effects. In this paper, we examine ...
Analysis of interval-censored recurrent event processes subject to resolution
Interval-censored recurrent event data arise when the event of interest is not readily observed but the cumulative event count can be recorded at periodic assessment times. In some settings, chronic disease processes may ...