Recursive residuals for linear mixed models

被引：0
作者：
Bani-Mustafa A. [1 ]
Matawie K.M. [2 ]
Finch C.F. [3 ]
Al-Nasser A. [4 ]
Ciavolino E. [5 ]
机构：
[1] Department of Mathematics, Australian College of Kuwait, Safat
[2] School of Computing, Engineering and Mathematics, Western Sydney University, Sydney, NSW
[3] School of Medical and Health Sciences, Edith Cowan University, Joondalup
[4] Department of Statistics, Faculty of Science, Yarmouk University, Irbid
[5] University of Salento, Lecce
来源：
Quality & Quantity | 2019年 / 53卷 / 3期
基金：
英国医学研究理事会;
关键词：
BLUP; Fitting-of-constant; Linear mixed model; Recursive estimation; Recursive residuals;
D O I：
10.1007/s11135-018-0814-6
中图分类号：
学科分类号：
摘要：
This paper presents and extends the concept of recursive residuals and their estimation to an important class of statistical models, Linear Mixed Models (LMM). Recurrence formulae are developed and recursive residuals are defined. Recursive computable expressions are also developed for the model’s likelihood, together with its derivative and information matrix. The theoretical framework for developing recursive residuals and their estimation for LMM varies with the estimation method used, such as the fitting-of-constants or the Best Linear Unbiased Predictor method. These methods are illustrated through application to an LMM example drawn from a published study. Model fit is assessed through a graphical display of the developed recursive residuals and their Cumulative Sums. © 2018, Springer Nature B.V.
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收藏
页码：1263 / 1274
页数：11
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