[R-meta] [R=meta] Question about removal of outliers and power calculation

Michael Dewey ||@t@ @end|ng |rom dewey@myzen@co@uk
Tue Jul 30 12:46:41 CEST 2019


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.

> 2. I wonder whether any one of you are familiar with any tools to calculate
> 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).


> Thank you very much!
> 
> Regards,
> Joanne
> 
> 	[[alternative HTML version deleted]]
> 
> _______________________________________________
> R-sig-meta-analysis mailing list
> R-sig-meta-analysis using r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis
> 
> ---
> This email has been checked for viruses by AVG.
> https://www.avg.com
> 
> 

-- 
Michael
http://www.dewey.myzen.co.uk/home.html



More information about the R-sig-meta-analysis mailing list