[R-meta] Facing some issues on Meta - regression

[Michael Dewey]

It would be easier to help you if you (a) showed your data using dput(), 
(b) pasted your actual code rather than showing a screenshot which means 
having to type it all in again.

Having said that I believe that the plot functions in meta have an 
argument to backtransform the estimates. From the help for bubble

Backtransf

A logical indicating whether results for relative summary measures 
(argument sm equal to "OR", "RR", "HR", or "IRR") should be back 
transformed. If backtransf=TRUE, results for sm="OR" are printed as odds 
ratios rather than log odds ratios, for example.

Michael

On 11/08/2024 20:28, Sancho Xavier via R-sig-meta-analysis wrote:
> Hi everyone, I hope you're all doing well.
> I need your help with something. I'm applying a meta-regression on a 
> dataset where I initially used the |metaprop| function to obtain the 
> pooled proportions of hypertension. Now, I'm trying to understand how 
> variables like the year of publication, study type, and publication 
> pathways influence the effect size (proportion) in the meta-analysis.
> Dataset (called "hiper")
> 
> Here are the scripts I used:
> First, I applied |metaprop|:
> 
> Next, I applied the meta-regression:
> 
> After generating the plot (see below), I noticed that without 
> transforming the |TE| and |seTE| values, the proportions on the x-axis 
> appear as negative values. I would like to know if my scripts for the 
> meta-regression are correct and whether it would be necessary to apply a 
> logarithmic transformation (|transf.ilogit(m.prop$TE)| and 
> |transf.ilogit(m.prop$seTE)|) to fix this.
> Additionally, I would appreciate your advice on which method is more 
> appropriate: using the transformed values or the non-transformed ones?
> 
>   Thanks in advance for your help!
> Best wishes,
> 
> *Sancho Xavier*
> Candidate for Postgraduate Programme in Epidemiology in Public Health
> MBA in Data Science and Analytics at USP (ongoing)
> *Linkedin:* linkedin.com/in/sancho-xavier-59565a18a
> *Orcid iD:* https://orcid.org/0000-0001-9493-4098
> *Web of Science (Clarivate):* 
> https://www.webofscience.com/wos/author/record/GON-5675-2022 
> <https://www.webofscience.com/wos/author/record/GON-5675-2022>
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