Bivariate linear mixed models using SAS proc MIXED

被引：88

作者：

Thiébaut, R

Jacqmin-Gadda, H

Chêne, G

Leport, C

Commenges, D

机构：

[1] Univ Bordeaux 2, INSERM, Unite 330, ISPED, F-33076 Bordeaux, France

[2] Hop Bichat Claude Bernard, F-75877 Paris 18, France

来源：

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE | 2002年 / 69卷 / 03期

关键词：

bivariate random effects model; bivariate first order auto-regressive process; SAS proc MIXED; HIV infection;

D O I：

10.1016/S0169-2607(02)00017-2

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

引用

页码：249 / 256

页数：8

共 15 条

[1] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].