I would STRONGLY recommend that you talk to your local statistician.

Further:

1. R-help is not a statistical consulting forum
2. Remote statistical consulting is very risky due to the inherent
difficulty in communicating all essential context of the problem and data.

You have been warned!

-- Bert

On Tue, Jul 17, 2012 at 2:10 AM, natalie.vanzuydam <nvanzuydam@gmail.com>wrote:

> Hi,
>
> I'm hoping that someone will be able to help.  I would like to compare how
> covariates associate with the risk of a binary outcome during two periods.
> Period 1 will be non-exposure to a treatment and period 2 will be exposure
> to a treatment.  The same individuals will be examined in each group but I
> want to be able to compare the association of certain covariates between
> the
> two groups to see if there is a treatment interaction.  I've looked at
> case-crossover designs and time series analysis and don't think that they
> are suitable.  The cohort has longitudinal data so individuals will go onto
> treatment at different times and the effect of the treatment needs to be
> administered for a while before it has an effect.  The reason why I cannot
> just go ahead with an exposed vs unexposed design is that most individuals
> in the cohort end up on the treatment eventually and the unexposed group is
> very small and lacks power for a meaningful comparison.
>
> Is there anyway to compare the same individuals during different exposure
> times and to look at the effect of different covariates under the exposed
> and unexposed conditions?
>
> Thanks for you help,
> Natalie
>
> -----
> Natalie Van Zuydam
>
> PhD Student
> University of Dundee
> nvanzuydam@dundee.ac.uk
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Stats-question-Comparison-of-the-same-individuals-during-two-exposure-times-tp4636732.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 

Bert Gunter
Genentech Nonclinical Biostatistics

Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm

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