title: Multivariate t linear mixed models for irregularly observed multiple repeated measures with missing outcomes.
abstract: Missing outcomes or irregularly timed multivariate longitudinal data frequently occur in clinical trials or biomedical studies. The multivariate t linear mixed model (MtLMM) has been shown to be a robust approach to modeling multioutcome continuous repeated measures in the presence of outliers or heavy-tailed noises. This paper presents a framework for fitting the MtLMM with an arbitrary missing data pattern embodied within multiple outcome variables recorded at irregular occasions. To address the serial correlation among the within-subject errors, a damped exponential correlation structure is considered in the model. Under the missing at random mechanism, an efficient alternating expectation-conditional maximization (AECM) algorithm is used to carry out estimation of parameters and imputation of missing values. The techniques for the estimation of random effects and the prediction of future responses are also investigated. Applications to an HIV-AIDS study and a pregnancy study involving analysis of multivariate longitudinal data with missing outcomes as well as a simulation study have highlighted the superiority of MtLMMs on the provision of more adequate estimation, imputation and prediction performances.
authors.affiliation: Department of Statistics, Graduate Institute of Statistics and Actuarial Science, Feng Chia University, Taichung 40724, Taiwan. wlunwang@fcu.edu.tw
authors.forename: Wan-Lun
authors.initials: WL
authors.lastname: Wang
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000097:blood; D000328:Adult; D000465:Algorithms; D001499:Bayes Theorem; D002986:Clinical Trials as Topic; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies; D008875:Middle Aged; D015999:Multivariate Analysis; D011247:Pregnancy; D012367:RNA, Viral / Q000097:blood; D055815:Young Adult
chemical_list: D012367:RNA, Viral
keywords: AECM algorithm; Damped exponential model; Missing values; Outliers; Prediction