Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates

This book PDF is perfect for those who love Medical genre, written by Jeffrey R. Wilson and published by Springer Nature which was released on 28 September 2020 with total hardcover pages 182. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates books below.

Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates
Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates
Author : Jeffrey R. Wilson
File Size : 41,5 Mb
Publisher : Springer Nature
Language : English
Release Date : 28 September 2020
ISBN : 9783030489045
Pages : 182 pages
Get Book

Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates by Jeffrey R. Wilson Book PDF Summary

This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data, they can be used to analyze any kind of data that contain covariates that change over time. The included data are analyzed with the use of both R and SAS, and the data and computing programs are provided to readers so that they can replicate and implement covered methods. It is an excellent resource for scholars of both computational and methodological statistics and biostatistics, particularly in the applied areas of health. ​

Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates

Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates by Jeffrey R. Wilson,Elsa Vazquez-Arreola,(Din) Ding-Geng Chen

This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data,

Get Book
Innovative Statistical Methods for Public Health Data

Innovative Statistical Methods for Public Health Data by Ding-Geng (Din) Chen,Jeffrey Wilson

The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies

Get Book
Modeling Binary Correlated Responses using SAS SPSS and R

Modeling Binary Correlated Responses using SAS SPSS and R by Jeffrey R. Wilson,Kent A. Lorenz

Statistical tools to analyze correlated binary data are spread out in the existing literature. This book makes these tools accessible to practitioners in a single volume. Chapters cover recently developed statistical tools and statistical packages that are tailored to analyzing correlated binary data. The authors showcase both traditional and new

Get Book
Statistical Regression Modeling with R

Statistical Regression Modeling with R by Ding-Geng (Din) Chen,Jenny K. Chen

This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work

Get Book
Progress in Applied Mathematical Modeling

Progress in Applied Mathematical Modeling by Fengshan Yang

This book presents new research related to the mathematical modelling of engineering and environmental processes, manufacturing, and industrial systems. It includes heat transfer, fluid mechanics, CFD, and transport phenomena; solid mechanics and mechanics of metals; electromagnets and MHD; reliability modelling and system optimisation; finite volume, finite element, and boundary element

Get Book
Advances and Challenges in Parametric and Semi parametric Analysis for Correlated Data

Advances and Challenges in Parametric and Semi parametric Analysis for Correlated Data by Brajendra C. Sutradhar

This proceedings volume contains eight selected papers that were presented in the International Symposium in Statistics (ISS) 2015 On Advances in Parametric and Semi-parametric Analysis of Multivariate, Time Series, Spatial-temporal, and Familial-longitudinal Data, held in St. John’s, Canada from July 6 to 8, 2015. The main objective of the ISS-2015 was the discussion

Get Book
Generalized Estimating Equations

Generalized Estimating Equations by Andreas Ziegler

Generalized estimating equations have become increasingly popular in biometrical, econometrical, and psychometrical applications because they overcome the classical assumptions of statistics, i.e. independence and normality, which are too restrictive for many problems. Therefore, the main goal of this book is to give a systematic presentation of the original generalized

Get Book
Mixed Effects Models for Complex Data

Mixed Effects Models for Complex Data by Lang Wu

Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement

Get Book