Flexible longitudinal linear mixed models for multiple censored responses data.
In biomedical studies and clinical trials, repeated measures are often subject to some upper and/or lower limits of detection. Hence, the responses are either left or right censored. A complication arises when more than one series of responses is repeatedly collected on each subject at irregular int...
| Publicado en: | Statistics in Medicine Vol. 38; no. 6; pp. 1074 - 1103 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
Mar2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=134735605&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 134735605 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02776715 2DZ jtl: Statistics in Medicine issn: 02776715 maglogo: Y pubinfo: dt: Mar2019 vid: 38 iid: 6 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 134735605 134735605 NLM30421470 134735605 10.1002/sim.8017 NLM30421470 134735605 ppf: 1074 ppct: 29 formats: tig: atl: Flexible longitudinal linear mixed models for multiple censored responses data. aug: au: Lachos, Victor H. A. Matos, Larissa Castro, Luis M. Chen, Ming‐Hui Chen, Ming-Hui affil: Department of Statistics, University of Connecticut, Storrs Connecticut sug: subj: Linear Regression Prospective Studies Polymerase Chain Reaction Viral Load Statistics and Numerical Data Time Factors HIV Infections Multivariate Analysis Human Sensitivity and Specificity Algorithms Probability Validation Studies Comparative Studies Evaluation Research Multicenter Studies Scales ab: In biomedical studies and clinical trials, repeated measures are often subject to some upper and/or lower limits of detection. Hence, the responses are either left or right censored. A complication arises when more than one series of responses is repeatedly collected on each subject at irregular intervals over a period of time and the data exhibit tails heavier than the normal distribution. The multivariate censored linear mixed effect (MLMEC) model is a frequently used tool for a joint analysis of more than one series of longitudinal data. In this context, we develop a robust generalization of the MLMEC based on the scale mixtures of normal distributions. To take into account the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is considered. For this complex longitudinal structure, we propose an exact estimation procedure to obtain the maximum-likelihood estimates of the fixed effects and variance components using a stochastic approximation of the EM algorithm. This approach allows us to estimate the parameters of interest easily and quickly as well as to obtain the standard errors of the fixed effects, the predictions of unobservable values of the responses, and the log-likelihood function as a byproduct. The proposed method is applied to analyze a set of AIDS data and is examined via a simulation study. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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