Bivariate linear mixed models using SAS proc MIXED

TL;DR

This paper presents methods for fitting bivariate linear mixed models with SAS PROC MIXED, including random effects and auto-regressive processes, demonstrated through an HIV infection example.

Contribution

It provides practical codes, techniques, and discusses limitations for applying bivariate linear mixed models in SAS PROC MIXED.

Findings

Effective modeling of longitudinal data with two markers

Extension potential to multivariate responses

Application to HIV infection data

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.