I have a dataset which has a predictor (Temperature), a response
(Developmental Time) and two separate factors Species ( A & B) and
Population (High, Low, Middle). I want to compare whether the populations
and the species differ from each other (is A different from B or is low A
different to high A, but not necessarily together (e.g., Middle A is
different to Low B).

Theory suggests the data should be non-linear and follow a power function,
and indeed, it's neither linear or normally distributed. I can transform
both the predictor and the response by logs to correct this, and follow up
with an ANCOVA (DT~Temp*Pop, dataset=dataset), but I'm unsure whether this
is the most powerful method possible. I've tried using boxcox
transformations to simply transform the response, but to no avail.

In short, I want to compare different non-linear models to each other, but
have no idea how.

I would also like to know how to draw this non-linear model through a plot
(for High A, Middle A, Low A, High B & Low B)

Thanks,
D

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