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st: RE: RE: RE: effect size in nonlinear regression
From
Nick Cox <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
st: RE: RE: RE: effect size in nonlinear regression
Date
Tue, 16 Nov 2010 17:57:48 +0000
Very small but possibly not minor detail: it depends on your audience, but e as a parameter suggests to many exp(1) ~ 2.71828, so that some other symbol may be advisable.
Nick
[email protected]
Nick Cox
There seems to be some latent LaTeX lingering in your equation, but I guess that your curve shifts will not easily reduce to single numbers. I think you need graphs rather than global measures.
Airey, David C
I appreciate the replies, and sorry for not being clear.
Were I talking about a power analysis for the t-test and effect sizes,
I might talk in terms of Cohen's d, or (mean1 - mean2)/s, because I
have to capture the mean difference and the variation in the groups.
I was looking into power analysis of a 4 parameter log-logistic equation,
f(x) = c + frac{d-c}{1+exp(b(log(x)-log(e)))}
and was wondering about comparable effect size measures between two curves for
a difference in one of the parameters, that also captures the guassian variation around
the curves and the difference in the parameter.
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