Hi David:

My main goal is to be able to find the method/model that estimates the
random effect of site on multiple binomial outcomes in multicenter clinical
trial settings. The methods you have suggested are fixed effects models,
right?

Thanks
Anamika

On Sun, May 12, 2013 at 9:44 PM, David Winsemius <dwinsemius@comcast.net>wrote:

>
> On May 12, 2013, at 4:44 PM, Anamika Chaudhuri wrote:
>
> > Hi:
> >
> > I have asked this question on Cross-Validated. So it might be a cross
> > posting but havent received any responses to it.
> >
> > I am trying to see which distribution will best fit the data I am working
> > on. The dataset is as following:
> >
> >    Site          Nausea      headache        Abdominal Distension
> >    1                   17                   5                   10
> >    2                    12                   8                   7
> >    .....
> >
> > So each site has  total # adverse events for each type/category and have
> > equal # patients per site, say 60 and there are 63 sites. If I were to
> > analyze the data for multiple outcomes per site, the number of events per
> > category given the category response rates can be assumed to be
> > independently distributed. They can be modeled by a multinomial
> > distribution with parameters n=60 and category response rates pi1, . . .
> ,
> > piC for site i. The individual variation in category response rates can
> be
> > modeled by a Dirichlet distribution.
> >
> > Just wondering if I am thinking through this correctly.
> > If so, could someone share some thoughts on how this could be done in R?
>
> This is more of a statistical question, and I'm surprised no advice was
> offered on CrossValidated. I responded there. You should find that this
> sort of question is handled in "S-PLUS (and R) Manual to Accompany
> Agresti’s Categorical Data Analysis" (2002) 2nd edition by Laura A.
> Thompson, 2006©, which is very easy to find with a Google search.
>
> --
> David Winsemius
> Alameda, CA, USA
>
>

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