| 书目名称 | Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates |
| 编辑 | Jeffrey R. Wilson,Elsa Vazquez-Arreola,(Din) Ding- |
| 视频video | |
| 概述 | Features pioneering developments of computational and methodological statistics and biostatistics with applications to real and familiar datasets.Presents affiliated data and computer programs so that |
| 丛书名称 | Emerging Topics in Statistics and Biostatistics |
| 图书封面 |  |
| 描述 | .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. . |
| 出版日期 | Book 2020 |
| 关键词 | generalized method of moments estimators; GMM estimators; method of moments; estimators; GMM; correlated |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-48904-5 |
| isbn_softcover | 978-3-030-48906-9 |
| isbn_ebook | 978-3-030-48904-5Series ISSN 2524-7735 Series E-ISSN 2524-7743 |
| issn_series | 2524-7735 |
| copyright | Springer Nature Switzerland AG 2020 |
发表于 2025-3-21 16:16:01
