[R-meta] [R=meta] Question about removal of outliers and power calculation
c@thk|d@|over @end|ng |rom gm@||@com
Tue Jul 30 13:38:44 CEST 2019
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On Tue, Jul 30, 2019 at 6:46 PM Michael Dewey <lists using dewey.myzen.co.uk>
> Dear Joanne
> In line comments
> On 30/07/2019 04:21, Cath Kids wrote:
> > Hello everyone,
> > I am new to meta-analysis and I would like to clarify some conceptual
> > matter:
> > 1. Should I remove outliers before doing subgroup analysis/ meta
> > regression? In my study, heterogeneity became insignificant after removal
> > outliers. I read meta-analyses which did both practice and I wonder which
> > is the correct way.
> This raises a number of issues. If heterogeneity exists why do you want
> to reduce or eliminate it? Would it not be better to try to describe and
> explain it? In general removing outliers leads to a model which is data
> dependent rather than the scientific model you started with. The only
> time I would contemplate removing observations would be if there was
> reason to suspect that they are fraudulent, recorded erroneously, did
> not really meet the inclusion criteria after all, or some other
> principled explanation which i cannot think of just now.
I see. So I should use all observations for the subgroup analysis/
meta-regression. But then given the heterogeneity of the results, I can
remove the outliers and check whether there is any change in the overall
effect size as a sensitivity analysis. is that right?
> > 2. I wonder whether any one of you are familiar with any tools to
> > power for meta-analysis of correlation coefficients?
> If you are planning a study why do you need power? The number of primary
> studies you find in your literature search is not within your powers to
> choose. You can only analyse what you find, not what you would like to
> find. If you have already done the study then all the required
> information about precision is contained within the confidence estimates
> about your estimate(s).
> I refer to this guideline online
However, it does not mention meta-analysis of correlation. So I'm not sure
how to do it.
> > Thank you very much!
> > Regards,
> > Joanne
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