First Hitting Time Regression Models

Lifetime Data Analysis Based on Underlying Stochastic Processes
Product Number: EB00742453
Released: Nov 15, 2018
Business Term: Purchase
ISBN: #9781119437222
Publisher: Wiley-ISTE
Please log in to view pricing

Description

This book aims to promote regression methods for analyzing lifetime (or time-to-event) data that are based on a representation of the underlying process, and are therefore likely to offer greater scientific insight compared to purely empirical methods. In contrast to the rich statistical literature, the regression methods actually employed in lifetime data analysis are limited, particularly in the biomedical field where D. R. Cox's famous semi-parametric proportional hazards model predominates. Practitioners should become familiar with more flexible models. The first hitting time regression models (or threshold regression) presented here represent observed events as the outcome of an underlying stochastic process. One example is death occurring when the patient's health status falls to zero, but the idea has wide applicability - in biology, engineering, banking and finance, and elsewhere. The central topic is the model based on an underlying Wiener process, leading to lifetimes following the inverse Gaussian distribution. Introducing time-varying covariates and many other extensions are considered. Various applications are presented in detail.

x-large
Author(s): Chrysseis Caroni
Genre: Science
Original Publish Date: Jul 17, 2017

Sign up for our email newsletter