Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates (Hardcover, 1st ed. 2020)

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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.

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Product Description

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.

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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Emerging Topics in Statistics and Biostatistics

Release date

October 2020

Availability

Expected to ship within 10 - 15 working days

First published

2020

Authors

, ,

Dimensions

235 x 155mm (L x W)

Format

Hardcover

Pages

166

Edition

1st ed. 2020

ISBN-13

978-3-03-048903-8

Barcode

9783030489038

Categories

LSN

3-03-048903-5



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