Piecewise Exponential Models for Survival Data with Covariates
نویسندگان
چکیده
منابع مشابه
Informative Censoring in Piecewise Exponential Survival Models
There are often reasons to suppose that there is dependence between the time to event and time to censoring, or informative censoring, for survival data, particularly when considering medical data. This is because the decision to treat or not is often made according to prognosis, usually with the most ill patients being prioritised. Due to identifiability issues, sensitivity analyses are often ...
متن کاملMultivariate Frailty Models for Exchangeable Survival Data with Covariates
We consider a multivariate lognormal frailty model for correlated exchangeable failure time data, where the marginal lifetimes have conditional Weibull distributions. We discuss Bayesian statistical methods to fit this model to experimental data with varying cluster sizes. The Bayesian inferential approach arises naturally from the hierarchical structure of the frailty model. In contrast, imple...
متن کاملCox Regression Models with Functional Covariates for Survival Data.
We extend the Cox proportional hazards model to cases when the exposure is a densely sampled functional process, measured at baseline. The fundamental idea is to combine penalized signal regression with methods developed for mixed effects proportional hazards models. The model is fit by maximizing the penalized partial likelihood, with smoothing parameters estimated by a likelihood-based criter...
متن کاملAdditive risk models for survival data with high-dimensional covariates.
As a useful alternative to Cox's proportional hazard model, the additive risk model assumes that the hazard function is the sum of the baseline hazard function and the regression function of covariates. This article is concerned with estimation and prediction for the additive risk models with right censored survival data, especially when the dimension of the covariates is comparable to or large...
متن کاملa new approach to credibility premium for zero-inflated poisson models for panel data
هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...
15 صفحه اولذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 1982
ISSN: 0090-5364
DOI: 10.1214/aos/1176345693