[图书][B] Handbook of survival analysis
JP Klein, HC Van Houwelingen, JG Ibrahim… - 2014 - api.taylorfrancis.com
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 …
data analysis. This area of statistics deals with time-to-event data which is complicated not …
A unified framework for fitting Bayesian semiparametric models to arbitrarily censored survival data, including spatially referenced data
ABSTRACT A comprehensive, unified approach to modeling arbitrarily censored spatial
survival data is presented for the three most commonly used semiparametric models …
survival data is presented for the three most commonly used semiparametric models …
Bayesian spatial survival models
Survival analysis has received a great deal of attention as a subfield of Bayesian
nonparametrics over the last 50 years. In particular, the fitting of survival models that allow …
nonparametrics over the last 50 years. In particular, the fitting of survival models that allow …
Childhood mortality in sub-Saharan Africa: cross-sectional insight into small-scale geographical inequalities from Census data
Objectives To estimate and quantify childhood mortality, its spatial correlates and the impact
of potential correlates using recent census data from three sub-Saharan African countries …
of potential correlates using recent census data from three sub-Saharan African countries …
A Bayesian hierarchical model for related densities by using Pólya trees
J Christensen, L Ma - Journal of the Royal Statistical Society …, 2020 - academic.oup.com
Bayesian hierarchical models are used to share information between related samples and to
obtain more accurate estimates of sample level parameters, common structure and variation …
obtain more accurate estimates of sample level parameters, common structure and variation …
Multiscale spatial density smoothing: an application to large-scale radiological survey and anomaly detection
We consider the problem of estimating a spatially varying density function, motivated by
problems that arise in large-scale radiological survey and anomaly detection. In this context …
problems that arise in large-scale radiological survey and anomaly detection. In this context …
Bayesian spatio‐temporal survival analysis for all types of censoring with application to a wildlife disease study
K Yao, J Zhu, DJ O'Brien, D Walsh - Environmetrics, 2023 - Wiley Online Library
In this article, we consider modeling arbitrarily censored survival data with spatio‐temporal
covariates. We demonstrate that under the piecewise constant hazard function, the …
covariates. We demonstrate that under the piecewise constant hazard function, the …
Generalized accelerated failure time spatial frailty model for arbitrarily censored data
Flexible incorporation of both geographical patterning and risk effects in cancer survival
models is becoming increasingly important, due in part to the recent availability of large …
models is becoming increasingly important, due in part to the recent availability of large …
[HTML][HTML] Modelling county level breast cancer survival data using a covariate-adjusted frailty proportional hazards model
Understanding the factors that explain differences in survival times is an important issue for
establishing policies to improve national health systems. Motivated by breast cancer data …
establishing policies to improve national health systems. Motivated by breast cancer data …
Survival analysis of loblolly pine trees with spatially correlated random effects
Loblolly pine, a native pine species of the southeastern United States, is the most-planted
species for commercial timber. Predicting survival of loblolly pine following planting is of …
species for commercial timber. Predicting survival of loblolly pine following planting is of …