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Dynamic Regression Models for Survival Data

This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and;

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Dynamic Regression Models for Survival Data

This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and;

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Dynamic Prediction in Clinical Survival Analysis

in dynamic prediction Part IV explores dynamic prediction models for survival data using genomic data Dynamic Prediction in Clinical Survival;

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Dynamical Biostatistical Models

regression models that include the time dimension, such as mixed-effect models, survival models, multistate models, and joint models for repeated;

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Regression With Social Data

response models* Poisson, negative binomial, and other regression models for event-count data* Survival analysis using multistate, multiepisode;

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Regression Models as a Tool in Medical Research

logistic regression model for binary outcomes, and the Cox proportional hazards model for survival data. The text emphasizes adequate use, correct;

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Regression Models As A Tool In Medical Research

logistic regression model for binary outcomes, and the Cox proportional hazards model for survival data. The text emphasizes adequate use, correct;

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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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Regression Modeling Strategies

for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi;

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Regression Modeling Strategies

for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi;

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Survival Analysis Using S

Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival;

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Regression Analysis of Survival Data in Cancer Chemotherapy

This book presents ideas and procedures for regression analysis of survival data in cancer chemotherapy based on regression-based;

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Handbook for Applied Modeling

Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data;

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Handbook for Applied Modeling

Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data;

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Regression Models For Time Series Analysis

models (GLM) which provides, under some conditions, a unified regression theory suitable for continuous, categorical, and count data. The authors;

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Survival Analysis Using the Sas System

Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul D. Allison, is an accessible, data;

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Event History Analysis with R

chapters, Explanatory Variables and Regression, and Register- Based Survival Data Models. The book has been restructured to improve the flow, and;

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Forecasting with Dynamic Regression Models

This volume presents the basic concepts and practice of building, using and interpreting single equation dynamic regression models (also;

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Applied Survival Analysis

Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical;

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An Introduction to Generalized Linear Models

focusing on methods for analyzing particular kinds of data. It covers normal, Poisson, and binomial distributions; linear regression models;

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Modeling Microbial Responses in Food

The first state-of-the-art review of this dynamic field in a decade, Modeling Microbial Responses in Foods provides the latest information;

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Modeling Microbial Responses in Food

The first state-of-the-art review of this dynamic field in a decade, Modeling Microbial Responses in Foods provides the latest information;

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Statistical Models For Causal Analysis

, logistic regression, multinomial logistic regression and survival models. The goal is to impart a working knowledge of these models with a minimum;

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Empirical Likelihood Method in Survival Analysis

empirical likelihood method for right censored survival data. The author uses R for calculating empirical likelihood and includes many worked out;

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Empirical Likelihood Method in Survival Analysis

empirical likelihood method for right censored survival data. The author uses R for calculating empirical likelihood and includes many worked out;

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Survival Analysis Using SAS

Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul Allison, is an accessible, data;

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Survival and Event History Analysis

The aim of this book is to bridge the gap between standard textbook models and a range of models where the dynamic structure of the data;

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