[R-meta] The effect size of a moderator in a meta-regression
@ngelinet@ui @ending from gm@il@com
Tue Jul 31 18:01:47 CEST 2018
Thank you so much for your reply. Yes, I agree that we should interpret the
magnitude of the effect size in the context of research area and overall
On Tue, Jul 31, 2018 at 11:10 AM, Michael Dewey <lists using dewey.myzen.co.uk>
> Dear Angeline
> Comments inline below
> On 30/07/2018 18:08, Angeline Tsui wrote:
>> Hello all,
>> I have a question about the effect size of a moderator in a
>> In my meta-analysis, I used Cohen's d as the effect size, I ran a
>> meta-regression with a number of moderators (i.e., like a multiple
>> regression). I recently have received a feedback of a reviewer asking me
>> specifically how to interpret the magnitude of the effect size of a
>> significant moderator. In this case, the beta coefficient of this is about
>> 0.19 and the weighted mean effect size of this meta-analysis is fairly low
>> (around 0.3 but it is significant).
>> So my question is how to interpret the magnitude of the beta coefficient
>> here? In the context of a small weighted effect size, it is fairly large,
>> for example, a unit change of x1 will lead to 0.19 increase in the Cohen's
>> d (holding all other moderators constant). In terms of percentage, it is a
>> large increase, approximately 63% increase (i.e., 0.19/0.3). However, in
>> terms of the "rule of thumb" of Cohen's d size, it is small, as 0.2 is
>> small Cohen's d.
> I would prefer the first of these as it puts it in the context of the
> overall picture. You would be less impressed by a coefficient of 0.19 if
> the summary were 1.3 rather than 0.3.
> Disclaimer: I find Cohen's rule of thumb very unhelpful even though I am
> sure he meant well.
>> What do you think? Do you think that I should interpret the size of beta
>> coefficient in the context of the weighted mean effect size or stick to
>> Cohen's d rule of thumb?
>> Thanks very much and I look forward to receiving your reply.
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