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Estimation and prediction in linear mixed models with skew‐normal random effects for longitudinal data
Author(s) -
Lin Tsung I.,
Lee Jack C.
Publication year - 2007
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3026
Subject(s) - skewness , random effects model , multivariate statistics , skew , statistic , statistics , generalized linear mixed model , mathematics , skew normal distribution , computer science , generalized linear model , econometrics , medicine , telecommunications , meta analysis
This paper extends the classical linear mixed model by considering a multivariate skew‐normal assumption for the distribution of random effects. We present an efficient hybrid ECME‐NR algorithm for the computation of maximum‐likelihood estimates of parameters. A score test statistic for testing the existence of skewness preference among random effects is developed. The technique for the prediction of future responses under this model is also investigated. The methodology is illustrated through an application to Framingham cholesterol data and a simulation study. Copyright © 2007 John Wiley & Sons, Ltd.