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Analysis of Survival Data with Dependent Censoring

This book introduces readers to copula-based statistical methods for analyzing survival data involving dependent censoring. Primarily;

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Survival Analysis in Medicine and Genetics

Using real data sets throughout, Survival Analysis in Medicine and Genetics introduces the latest methods for analyzing high-dimensional;

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Survival Analysis in Medicine and Genetics

Using real data sets throughout, Survival Analysis in Medicine and Genetics introduces the latest methods for analyzing high-dimensional;

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Survival Analysis

A concise summary of the statistical methods used in the analysis of survival data with censoring. Emphasizes recently developed;

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Survival Analysis Using the Sas System

-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with;

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Handbook of Survival Analysis

Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals;

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Handbook of Survival Analysis

Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals;

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Survival Analysis Using SAS

-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with;

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Analysis for Time-to-Event Data under Censoring and Truncation

Survival Analysis for Bivariate Truncated Data provides readers with a comprehensive review on the existing works on survival analysis;

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Modelling Survival Data in Medical Research

Modelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range;

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Survival Analysis with Interval-Censored Data

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical;

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Survival Analysis with Interval-Censored Data

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical;

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Hybrid Censoring Models Methods & Apps

methodology, life-testing procedures, and lifetime data analysis provides only hybrid censoring schemes, with little information about hybrid;

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Mixed Effects Models for Complex Data

semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values;

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Mixed Effects Models for Complex Data

semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values;

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An Introduction to Survival Analysis Using Stata, Revised Third Edition

An Introduction to Survival Analysis Using Stata, Revised Third Edition is the ideal tutorial for professional data analysts who want to;

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Dynamic Prediction in Clinical Survival Analysis

background. The book consists of four parts: Part I deals with prognostic models for survival data using (clinical) information;

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Survival Analysis

with the basic concepts of survival analysis-time to an event as a variable, censored data, and the hazard function-the author then introduces;

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Statistical Topics and Stochastic Models for Dependent Data with Applications

corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov;

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Flexible Parametric Survival Analysis Using Stata

the modeling of time-dependent and continuous covariates and looks at how relative survival can be used to measure mortality associated with a;

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Survival Analysis Using SAS

This volume is an accessible, data-based introduction to methods of survival analysis. Researchers who want to analyze survival data with;

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Missing and Modified Data in Nonparametric Estimation

book cover basic cases of direct data, biased data, nondestructive and destructive missing, survival data modified by truncation and censoring;

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Missing and Modified Data in Nonparametric Estimation

book cover basic cases of direct data, biased data, nondestructive and destructive missing, survival data modified by truncation and censoring;

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Survival Analysis

applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed;

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Joint Modeling of Longitudinal and Time-to-Event Data

survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological;

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Joint Modeling of Longitudinal and Time-to-Event Data

survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological;

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Practical Guides to Biostatistics and Epidemiology

This practical guide to survival data and its analysis for readers with a minimal background in statistics shows why the analytic methods;

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