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

種類:

電子ブック

責任表示:

by Jeffrey R. Wilson, Elsa Vazquez-Arreola, (Din) Ding-Geng Chen

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2020

著者名:

• Wilson, Jeffrey R.
• Vazquez-Arreola, Elsa.
• Chen, (Din) Ding-Geng.
• SpringerLink (Online service)

シリーズ名:

Emerging Topics in Statistics and Biostatistics ;

ISBN:

9783030489045 [3030489043]    

注記:

1. Introduction to Binary Regression Models -- 2. Generalized Estimating Equations Binary Models -- 3. Lai and Small Models for Time-Dependent Covariates -- 4. Lalonde, wilson, and Yin Models for Time-Dependent Covariates -- 5. Irimata, Broatch, and Wilson Models for Time-Dependent Covariates -- 6. Bayesian GMM to IBW Method of Analysis -- 7. Models for Joint Responses for Time-Dependent Covariates -- 8. Other Models for Time-Dependent Covariates.
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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