That's an interesting note. I'm not sure why it makes
good sense, to divide the ln(OR) by 1.81. But the
writer does make good sense in suggesting that a
good measure of effect size is log(OR), and what you
need for further information is not the N, but the
standard error. (I think he is suggesting that.)
The original question was about converting an OR
to a chi-squared test, in the context of meta-analysis.
I doubt why anyone should want to do that, except
as an intermediate step to finding the error term --
the chi-squared statistic itself is a *test* statistic, and
is poorly suited for "effect size". Where it is appropriate,
the OR is a fine measure of effect, and log(OR) is the
version that serves as an interval-scaled measure.
--
Rich Ulrich
Date: Sat, 30 Jun 2012 07:44:43 -0700
From:
[hidden email]
Subject: Re: odds ratio to chi square conversion
To:
[hidden email]
FYI:
~~~~~~~~~~~
Scott R Millis, PhD, ABPP, CStat, PStat®
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