| 书目名称 | Dynamic Mixed Models for Familial Longitudinal Data |
| 编辑 | Brajendra C. Sutradhar |
| 视频video | |
| 概述 | Provides a clear direction for accurate familial and longitudinal data analysis by presenting differences between the familial and longitudinal correlation models.Deals with non-stationary longitudina |
| 丛书名称 | Springer Series in Statistics |
| 图书封面 |  |
| 描述 | .This book provides a theoretical foundation for the analysis of discrete data such as count and binary data in the longitudinal setup. Unlike the existing books, this book uses a class of auto-correlation structures to model the longitudinal correlations for the repeated discrete data that accommodates all possible Gaussian type auto-correlation models as special cases including the equi-correlation models. This new dynamic modelling approach is utilized to develop theoretically sound inference techniques such as the generalized quasi-likelihood (GQL) technique for consistent and efficient estimation of the underlying regression effects involved in the model, whereas the existing ‘working’ correlations based GEE (generalized.estimating equations) approach has serious theoretical limitations both for consistent and efficient estimation, and the existing random effects based correlations approach is not suitable to model the longitudinal correlations. The book has exploited the random effects carefully only to model the correlations of the familial data. Subsequently, this book has modelled the correlations of the longitudinal data collected from the members of a large number of ind |
| 出版日期 | Book 20111st edition |
| 关键词 | GEE approaches and drawbacks; Generalized linear longitudinal mixed models (GLLMM); Generalized linear |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4419-8342-8 |
| isbn_softcover | 978-1-4614-2801-5 |
| isbn_ebook | 978-1-4419-8342-8Series ISSN 0172-7397 Series E-ISSN 2197-568X |
| issn_series | 0172-7397 |
| copyright | Springer Science+Business Media, LLC 2011 |
发表于 2025-3-21 16:52:08
