[R-meta] [SPAM](FN) Re: Facing some issues on Meta - regression

[Dr. Gerta Rücker]

Hi,

Michael is right with the argument backtransf, in principle. For example, for metabin(), bubble.metareg() takes the summary measure (e.g., "RR") from the metabin object, see code below. However, this doesn't seem to work with metaprop(), as also seen using the code below. @Guido?

Best,
Gerta

# metabin()

data(Olkin1995)
m1 <- metabin(ev.exp, n.exp, ev.cont, n.cont,
              data = Olkin1995, 
              studlab = paste(author, year),
              method = "Inverse")
m1$sm
mr1 <- metareg(m1, year)
mr1$sm          # NULL
mr1$.meta$x$sm  # "RR"
bubble(mr1)     # log scale automatically applied

# It is different for metaprop():

event <- c(81, 15, 1, 1, 60, 7)
n <- c(263, 148, 20, 29, 300, 20)
m2 <- metaprop(event, n) 
m2$sm
covar <- rnorm(length(n))
mr2<- metareg(m2, covar)
mr2$sm                         # NULL 
mr2$.meta$x$sm                 # "PLOGIT"
bubble(mr2)
bubble(mr2, backtransf = TRUE) # Doesn't work!
m2a$sm <- "PLOGIT"
bubble(mr2, backtransf = TRUE) # Still doesn't work!



UNIVERSITÄTSKLINIKUM FREIBURG
Institute for Medical Biometry and Statistics

Dr. Gerta Rücker
Guest Scientist

Stefan-Meier-Straße 26 · 79104 Freiburg
gerta.ruecker using uniklinik-freiburg.de

https://www.uniklinik-freiburg.de/imbi-en/employees.html?imbiuser=ruecker


-----Ursprüngliche Nachricht-----
Von: Michael Dewey via R-sig-meta-analysis <r-sig-meta-analysis using r-project.org> 
Gesendet: Montag, 12. August 2024 13:04
An: R Special Interest Group for Meta-Analysis <r-sig-meta-analysis using r-project.org>
Cc: Michael Dewey <lists using dewey.myzen.co.uk>
Betreff: [SPAM](FN) Re: [R-meta] Facing some issues on Meta - regression

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>
> *Reference Citation Analysis (RCA): 
> *https://referencecitationanalysis.com/00001471 
> <https://referencecitationanalysis.com/00001471>
> *Whatsapp: *+258 852255846
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