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Data Analysis Using Hierarchical Generalized Linear Models with R

advanced statistical modelling including generalized linear models with random effects, survival analysis and frailty models, multivariate HGLMs;

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Data Analysis Using Hierarchical Generalized Linear Models with R

advanced statistical modelling including generalized linear models with random effects, survival analysis and frailty models, multivariate HGLMs;

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Mixture Modelling for Medical and Health Sciences

typical daily problems to complex data modelling. Emphasis on the use of a wide variety of component densities for statistical modelling;

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Mixture Modelling for Medical and Health Sciences

of component densities for statistical modelling. Coverage of the latest random-effects models in modelling complex correlated data;

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Statistical Modelling of Survival Data with Random Effects

This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h;

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Statistical Modelling and Analysis Techniques

Statistical Modelling and Analysis Techniques provides insights into modelling and analytic aspects of random events and discusses;

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Modeling Survival Data

This book is for statistical practitioners, particularly those who design and analyze studies for survival and event history data. Building;

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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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Multi-State Survival Models for Interval-Censored Data

of stochastic processes. Multi-State Survival Models for Interval-Censored Data shows that the statistical modelling is versatile and allows for a wide;

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Multi-State Survival Models for Interval-Censored Data

of stochastic processes. Multi-State Survival Models for Interval-Censored Data shows that the statistical modelling is versatile and allows for a wide;

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Statistical Modelling in Biostatistics and Bioinformatics

and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling;

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Statistical Modelling in Biostatistics and Bioinformatics

and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling;

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Data Analysis with Stata

modelling concepts and their application. What You Will Learn * Perform important statistical tests to become a STATA data scientist * Be;

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Probability and Statistical Inference

inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these topics in an accessible;

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Probability and Statistical Inference

inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these topics in an accessible;

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Handbook Of Statistical Analyses Using Stata

each chapter with descriptions of the data and the statistical techniques to be used. The methods covered include descriptives, simple tests;

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Handbook of Statistical Analyses Using Stata, Fourth Edition

each chapter with descriptions of the data and the statistical techniques to be used. The methods covered include descriptives, simple tests;

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Handbook of Statistical Analyses Using Stata

each chapter with descriptions of the data and the statistical techniques to be used. The methods covered include descriptives, simple tests;

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A Handbook of Statistical Analyses Using Stata

each chapter with descriptions of the data and the statistical techniques to be used. The methods covered include descriptives, simple tests;

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Statistical Mechanics & Random Walks

In this book, the authors gather and present topical research in the study of statistical mechanics and random walk principles and;

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Computer Age Statistical Inference

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data;

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Generalized, Linear, and Mixed Models

An accessible and self-contained introduction to statistical models-now in a modernized new edition Generalized, Linear, and Mixed Models;

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Computer Age Statistical Inference, Student Edition

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and;

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Multiple-point Geostatistics

book provides an overview of this new field in three parts. Part I presents a conceptual comparison between traditional random function theory;

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Generalized Linear Models with Random Effects

. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood;

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Mixed Effects Models & Extensions Ecolog

This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are;

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