[R-sig-ME] Mixed model with multiple response variables?

David Duffy David.Duffy at qimr.edu.au
Tue Aug 5 23:31:41 CEST 2008

On Tue, 5 Aug 2008, Gang Chen wrote:

> Hi,
> I have a data set collected from 10 measurements (response variables)
> on two groups (healthy and patient) of subjects performing 4 different
> tasks. In other words there are two fixed factors (group and task),
> and 10 response variables. I could analyze the data with aov() or
> lme() in package nlme for each response variable separately, but since
> most likely there are correlations among the 10 response variables,
> would it be more meaningful to run a MANOVA? However manova() in R
> seems not to allow an error term in the formula. What else can I try
> for this kind of multivariate mixed model?

You might look at the Oct 2007 R-News article on the subject.  But a 
flexible approach is to use the sem package.

David Duffy.
| David Duffy (MBBS PhD)                                         ,-_|\
| email: davidD at qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
| Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v

More information about the R-sig-mixed-models mailing list