I'm not sure I understand.  If you fit an ANCOVA using the lm() function,
like this,
    fit <- lm(Y ~ X*as.factor(batch))
    summary(aov(fit))
and the hypothesis for equality of slopes is rejected, i.e., the
X:as.factor(batch)) term is significant, then this same model already has
batch-specific intercepts and slopes and a pooled mean squared error.  What
more do you need?

Jean


On Fri, May 31, 2013 at 5:41 AM, David A. <dasolexa@hotmail.com> wrote:

> Hi,
>
> I would like to compare two batches of a product over time to see if they
> behave similarly, i.e same slope and intercept. This is a stability study.
> I will be performing ANCOVA analysis for this. According to ICH and FDA
> guidelines, if the test rejects the hypothesis of equality of slopes, then
> I should fit a regression line to each batch where the intercept and the
> slope are the individual ones but I should use the pooled mean square error
> calculated from all batches.
>
> I wonder if anyone could help me to feed the calculated pooled mean square
> error in the function lm() or if there is another way to perform such
> analysis.
>
> Thanks for your help,
>
> Dave
>
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