bivariate logistic/probit with hierarchical structure
On Fri, 6 May 2011, Arthur Charpentier wrote:
I would like to fit a bivariate probit model, i.e. I observe Y=(Y1,Y2),
I have some covariates X1,...Xk, and I assume that there is a hierarchical
structure (and random effects), i.e. Y_i is actually a Y_{i,j} where j is a
subgroup index.
So this yield two correlations levels,
- within subgroup correlation between Y1_i's (if they belong to the same
subgroup)
Since you are doing "only" a bivariate, you might consider rewriting it as a univariate problem with appropriate random effects (that is Y1 and Y2 are in a lower level with variable specific random intercepts etc). This has been described previously sometime on this list. Just 2c, 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