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CRC Press Dynamic Prediction in Clinical Survival Analysis

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Description

Move beyond static survival models with Dynamic Prediction in Clinical Survival Analysis. While standard practice often relies on the Cox proportional hazards model to present static data regarding remaining lifetime after a diagnosis, this CRC Press monograph offers a different approach. This book focuses on dynamic models for predicting remaining lifetime at various later points in time, such as through the use of landmark models. This text is specifically designed to be useful to applied statisticians working with survival data. It addresses the vast amount of literature surrounding statistical models for diseases like cancer, cardiovascular disease, and chronic kidney disease by providing a framework for more responsive, time-dependent predictions. It is an essential resource for those looking to advance their understanding of clinical survival analysis and dynamic modeling.

Key Features

This CRC Press monograph focuses on dynamic models for predicting remaining lifetime at later points in time.

The text provides an alternative to standard static models based on the Cox proportional hazards model.

It covers methodologies such as landmark models to improve clinical survival analysis.

The content is designed to be useful to applied statisticians working with disease prediction data.

The book addresses survival prediction for various conditions including cancer and cardiovascular disease.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
10 November 2011
Listed Since
11 October 2010

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