Performing scientific investigations of poison exposure in the lab, we
have an experimental design with a  set of reference and a treated
samples (say A-samples and B-samples). We ad some chemical and measure
a response at several time intervals after the exposure � and at each
point in time A and B measurements are made in triplicate (response
could be concentration of a metabolite, number of living cells,  a
color or the like). We then make an XY (time/response) plot and fit a
curve (could be an exponential decay for example). As we measure in
triplicate at each time there is variation on each measurement point
on both A and B values. Though, in spite of fluctuations and
decreasing response for both the A and the B curve it seems that the A
response curve is higher than the B curve "most of the time"� How do
we make a statistical test of this? It should takes into account the
decay (response levels are not constant over time) and preferably the
variation in the triplets observations?

In a reply to a similar question (posted by Don Taylor to newsgroup
sci.stat.math 1997/05/26 ) it was suggested that in AUTOBOX the
problem could be treated as a 'POOLED CROSS-SECTIONAL TIME SERIES' �
however, it was not clear how to treat this problem in general (we do
not have AUTOBOX). Does anyone have a hint or reference how to solve
this problem?


Thanks in advance
.
.
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