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Data Analysis with Competing Risks and Intermediate States

Data Analysis with Competing Risks and Intermediate States explains when and how to use models and techniques for the analysis of competing;

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Data Analysis with Competing Risks and Intermediate States

Data Analysis with Competing Risks and Intermediate States explains when and how to use models and techniques for the analysis of competing;

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Multivariate Survival Analysis and Competing Risks

Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It;

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Multivariate Survival Analysis and Competing Risks

Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It;

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Competing Risks

is a real need for a book that presents an overview of methodology used in the interpretation and analysis of competing risks, with a focus on;

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Principles and Methods for Data Science

Principles and Methods for Data Science, Volume 43 in the Handbook of Statistics series, highlights new advances in the field, with;

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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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Multistate Models for the Analysis of Life History Data

Multistate Models for the Analysis of Life History Data provides the first comprehensive treatment of multistate modeling and analysis;

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Multistate Models for the Analysis of Life History Data

Multistate Models for the Analysis of Life History Data provides the first comprehensive treatment of multistate modeling and analysis;

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Lifetime Data

This book is meant for postgraduate modules that cover lifetime data in reliability and survival analysis as taught in statistics;

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Lifetime Data

This book is meant for postgraduate modules that cover lifetime data in reliability and survival analysis as taught in statistics;

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Retirement Timing and Social Stratification

-related financial pressures. This seminal study, derived from a statistical analysis of a large-scale survey data, provides a thorough;

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Interval-Censored Time-to-Event Data

analysis, and other models for interval-censored data. The next part presents interval-censored methods for current status data, Bayesian;

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Data Analysis Using SPSS

A concise introduction to data analysis for beginners and intermediate students using IBM - Statistical Package for Social Sciences (SPSS);

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Intermediate-Energy Nuclear Physics

* Devoted to discussing the interaction between hadrons with nuclei* Discusses experimental data and the methods and results of the;

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Quantitative Risk Analysis of Air Pollution Health Effects

characterizing and communicating remaining uncertainties. It shows how to apply modern data science, artificial intelligence and machine learning, causal;

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Quantitative Risk Analysis of Air Pollution Health Effects

characterizing and communicating remaining uncertainties. It shows how to apply modern data science, artificial intelligence and machine learning, causal;

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Survival Analysis Using S

log-linear models, while also detailing nonparametric procedures along with model building and data diagnostics. Medical and public health;

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Lifetime Data Statistical Models & Metho

This book is meant for postgraduate modules that cover lifetime data in reliability and survival analysis as taught in statistics;

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Epidemiology and Medical Statistics

assessing Biomarkers, analysis of competing risks; clinical trials including sequential and group sequential, crossover designs, cluster randomized;

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Transportation Safety Risks

collide with other vehicles or pedestrians, causing serious injuries or fatalities. According to data collected by the National Highway Traffic;

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Introduction to Hierarchical Bayesian Modeling for Ecological Data

become more complex and realistic through explanatory covariates and intermediate hidden states variables. When fitting the models to data, the;

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Introduction to Hierarchical Bayesian Modeling for Ecological Data

become more complex and realistic through explanatory covariates and intermediate hidden states variables. When fitting the models to data, the;

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IBM SPSS for Intermediate Statistics

linear modeling; multivariate analysis of variance (MANOVA); assessing reliability of data; multiple imputation; mediation, moderation, and;

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Ibm Spss For Intermediate Statistics

linear modeling; multivariate analysis of variance (MANOVA); assessing reliability of data; multiple imputation; mediation, moderation, and;

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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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