Smoothing Hazard Rates

نویسنده

  • Jane - Ling Wang
چکیده

The nonparametric approach to estimate hazard rates for lifetime data is flexible, model-free and data-driven. No shape assumption is imposed other than that the hazard function is a smooth function. Such an approach typically involves smoothing of an initial hazard estimate, with arbitrary choice of smoother. We describe methods for grouped lifetime data observed at certain time intervals and for continuously observed lifetime data. There are some intrinsic differences between the smoothing approaches for these two types of data. More specifically, smoothing an initial hazard estimate based on the life table is adopted for grouped lifetime data; while for continuous data, smoothing is employed to increments of the Nelson-Aalan cumulative hazard estimate aiming at the derivative of the cumulative hazard function. A few nonparametric hazard regression methods are also discussed.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

AN ADDITIVE MODEL FOR SPATIO-TEMPORAL SMOOTHING OF CANCER MORTALITY RATES

In this paper, a Bayesian hierarchical model is used to anaylze the female breast cancer mortality rates for the State of Missouri from 1969 through 2001. The logit transformations of the mortality rates are assumed to be linear over the time with additive spatial and age effects as intercepts and slopes. Objective priors of the hierarchical model are explored. The Bayesian estimates are quite ...

متن کامل

A Berry-Esseen Type Bound for a Smoothed Version of Grenander Estimator

In various statistical model, such as density estimation and estimation of regression curves or hazard rates, monotonicity constraints can arise naturally. A frequently encountered problem in nonparametric statistics is to estimate a monotone density function f on a compact interval. A known estimator for density function of f under the restriction that f is decreasing, is Grenander estimator, ...

متن کامل

A non-parametric method for hazard rate estimation in acute myocardial infarction patients: kernel smoothing approach.

BACKGROUND Kernel smoothing method is a non-parametric or graphical method for statistical estimation. In the present study was used a kernel smoothing method for finding the death hazard rates of patients with acute myocardial infarction. METHODS By employing non-parametric regression methods, the curve estimation, may have some complexity. In this article, four indices of Epanechnikov, Biqu...

متن کامل

Penalized spline smoothing in multivariable survival models with varying coefficients

The paper discusses penalised spline (P -spline) smoothing for hazard regression of multivariable survival data. Non-proportional hazard functions are fitted in a numerically handy manner by employing Poisson regression which results from numerical integration of the cumulative hazard function. Multivariate smoothing parameters are selected by utilizing the connection between P -spline smoothin...

متن کامل

bshazard: A Flexible Tool for Nonparametric Smoothing of the Hazard Function

The hazard function is a key component in the inferential process in survival analysis and relevant for describing the pattern of failures. However, it is rarely shown in research papers due to the difficulties in nonparametric estimation. We developed the bshazard package to facilitate the computation of a nonparametric estimate of the hazard function, with data-driven smoothing. The method ac...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003