John,
One more possibility, last one from me. Assuming your interest is in the
variance between batches, use either xtreg or gllamm.
Line up the results as Scott suggested, then do either xtreg or gllamm.
Rather than being interested in the significance of the coefficient on the
predictor assay, the outcome of interest would be the significance of
either sigma_u (xtreg) or the level two term "batch" in gllamm. In
gllamm, you could use -gllapred- with the ustd option to identify
specific outlier batches
xtreg assay1 assay2, i(batch)
or
gllamm assay1 assay2, i(batch) adapt
gllamm, allc
Buzz Burhans
>> I have two measures of batch performance on which I'd like to
>> perform a
>> regression. The measurements are taken on separate samples
>> from the batch,
>> and typically look something like:
>> Assay1 Assay2
>> Btch1 5400
>> Btch1 5320
>> Btch1 5670
>> Btch1 0.900
>> Btch1 0.905
>> Btch1 0.898
>> Btch2 8600
>> Btch2 7840
>> Btch2 7550
>> Btch2 0.962
>> Btch2 0.955
>> Btch2 0.943
>> ...etc (on for multiple batches which show correlated
>> measures for the two
>> assays)
>> -collapse- ing them to batch averages and then performing the
>> regression is
>> one approach, but it doesn't take variance of the measures
>> themselves into
>> account in the regression. Is there a system for performing
>> this type of
>> analysis?
>>
>
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