Hi Mahinda,

make sure to include previous correspondence so that we know what 
previous the previous suggestions are. Your analysis sounds technically 
correct if you can justify the 1, 2, and 5 values for the covariate. 
This design will give you a little more power.

doug



On 11/27/2012 01:28 PM, Mahinda Yogarajah wrote:
> Hi,
>
> Thanks for the reference and explanation of the subtle statistical 
> inferences. It was very useful.
>
> You are right in what i am trying to show (c- controls, p1 to p4 patients 
> with varying levels of endogenous factor) which is that when patients are 
> subdivided into levels of endogenous factor there is correlation with the 
> changes seen in dependent variables compared to controls. So far,
>
> C v whole P gp - differences seen in plausible areas.
> C v P1 (greatest endo factor) subgp  - no differences
> C v P4 subgp (lowest endo factor) - differences seen in plausible areas.
>
> Given that it is not valid to compare c v p1 and c v p4 (and p1 v p4 shows 
> nothing) is the following valid - perhaps it is similar to what you proposed:
>
> Consider c and p1 to p4 as one group of subjects (theoretically the only 
> difference between subjects being level of endogenous factor) but assign each 
> subject a variable which represents level of endoenous factor (c - 1 p1 - 2 
> p3 - 4 p4 - 5) - then run glm looking for correlation between endogenous 
> factor and dependent variable.
>
> Is this very different to what you suggested and any less valid ?
>
> Thanks.
>
> M
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