  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.
