I review assumptions about the missing-data mechanisms that underlie methods for the
statistical analysis of data with missing values. I describe Rubin's original definition of …

An up-to-date, comprehensive treatment of a classic text on missing data in statistics The
topic of missing data has gained considerable attention in recent decades. This new edition …

Several topics are addressed, including parametric models, semiparametric models based
on prior processes, proportional and non-proportional hazards models, frailty models, cure …

Clustered survival data are encountered in many scientific disciplines including human and
veterinary medicine, biology, epidemiology, public health and demography. Frailty models …

This volume examines modern techniques and research problems in the analysis of lifetime
data analysis. This area of statistics deals with time-to-event data which is complicated not …

Generalized likelihoods are commonly used to obtain consistent estimators with attractive
computational and robustness properties. Formally, any generalized likelihood can be used …

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R,
SAS, and BUGS provides the reader with a practical introduction into the analysis of interval …

Interval-Censored Time-to-Event Data: Methods and Applications collects the most recent
techniques, models, and computational tools for interval-censored time-to-event data. Top …

Bayesian Adaptive Randomized Trial Design for Patients With Recurrent Glioblastoma - PMC
Back to Top Skip to main content NIH NLM Logo Access keys NCBI Homepage MyNCBI …

This paper presents a unified treatment of Gaussian process models that extends to data
from the exponential dispersion family and to survival data. Our specific interest is in the …