Title

Recursive residuals for linear mixed models

Document Type

Journal Article

Publisher

Springer Netherlands

School

School of Medical and Health Sciences

Comments

Originally published as: Bani-Mustafa, A., Matawie, K. M., Finch, C. F., Al-Nasser, A., & Ciavolino, E. (2019). Recursive residuals for linear mixed models. Quality & Quantity, 53(3), 1263–1274. Original publication available here

Abstract

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.

DOI

10.1007/s11135-018-0814-6

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