Bivariate linear mixed models using SAS proc MIXED.

Rodolphe Thiébaut; Hélène Jacqmin-Gadda; Geneviève Chêne; Catherine Leport; Daniel Commenges

hal-00143963, version 1

Bivariate linear mixed models using SAS proc MIXED.

Rodolphe Thiébaut ( Author to contact preferably ) ^1, 2, Hélène Jacqmin-Gadda ², Geneviève Chêne ¹, Catherine Leport ³, Daniel Commenges ²

Comput Methods Programs Biomed 69, 3 (2002) 249-56

Abstract: Bivariate linear mixed models are useful when analyzing longitudinal data of two associated markers. In this paper, we present a bivariate linear mixed model including random effects or first-order auto-regressive process and independent measurement error for both markers. Codes and tricks to fit these models using SAS Proc MIXED are provided. Limitations of this program are discussed and an example in the field of HIV infection is shown. Despite some limitations, SAS Proc MIXED is a useful tool that may be easily extendable to multivariate response in longitudinal studies.

1: Epidémiologie, santé publique et développement
INSERM : U593 – IFR99 – Université Victor Segalen - Bordeaux II – ISPED
2: Biostatistique
INSERM : U875 – Université Victor Segalen - Bordeaux II
3: Service des maladies infectieuses et tropicales
Assistance publique - Hôpitaux de Paris (AP-HP) – Hôpital Bichat - Claude Bernard – Université Paris VII - Paris Diderot

hal-00143963, version 1
http://hal.archives-ouvertes.fr/hal-00143963
oai:hal.archives-ouvertes.fr:hal-00143963
From: Rodolphe Thiebaut <>
Submitted on: Thursday, 3 May 2007 22:44:15
Updated on: Friday, 4 May 2007 09:21:58

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arXiv: 0705.0568

PubMed: 12204452

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