Mixed Models

Research on mixed models has been extensive over the most recent decade. This book differs from the authors' previous monographs on longitudinal data in that it focuses on mixed models of a linear, generalized linear and nonlinear type. The book pays attention to recent developments that include diagnostics, semi-parametric methodology, non-normal random effects, multivariate longitudinal data, high-dimensional outcomes, joint modeling of longitudinal and survival data and discrimination and classification based on longitudinal data using mixed models.

過去十年來，對混合模型的研究非常廣泛。本書與作者之前關於長期資料的專著不同之處在於，它專注於線性、廣義線性和非線性類型的混合模型。本書關注最近的發展，包括診斷、半參數方法、非正態隨機效應、多變量長期資料、高維度結果、聯合建模長期和生存資料以及基於混合模型的長期資料的區分和分類。

Geert Verbeke is affiliated with KU Leuven.

Geert Molenberghs is affiliated with the University of Hasselt.

Verbeke and Molenberghs previously published two monographs on longitudinal data, dealing with continuous longitudinal data and the non-Gaussian counterpart.

Geert Verbeke 是與魯汶大學（KU Leuven）有關聯的。Geert Molenberghs 是與哈塞爾特大學（University of Hasselt）有關聯的。Verbeke 和 Molenberghs 先前出版了兩本關於長期資料的專著，分別處理連續長期資料和非高斯對應物。