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[R-meta] combining Means + SD at post, withD + 95% CI

4 messages · Jorge Teixeira, Michael Dewey, Dr. Gerta Rücker

Jorge Teixeira
# 
Hi all.

I did this to combine studies that provided M+SD, with others for which I
had only MD + 95% CI or p-value.


*Questions: *

i)   Is the Vi well calculated below, as the code was given by GPT?  n per
group is irrelevant here, right?

ii)  Is there a more elegant way to do this?

iii) Can this method backfire in some way or is there something in
particular that I should have in mind?


Thanks! Code below:

library(metafor)

#
dat <- structure(list(study = c("AA", "BB", "CC",
                                "EE", "DDD"), en = c(9, 41, 29, 8, 13
                                ), em = c(32, 27.5, 28.7, 22.8, 30.5), esd
= c(1.9, 3.8, 5.2,

   3.8, 4.9), cn = c(8, 26, 28, 10, 14), cm = c(30.1, 24.9, 26.9,

                                                24.7, 30.2), csd = c(2.4,
3.6, 3, 4.3, 5.1)), row.names = c(NA,


                                -5L), class = c("tbl_df", "tbl",
"data.frame"))

#
dat <- escalc(measure="MD", m1i=em, sd1i=esd, n1i=en, m2i=cm, sd2i=csd,
n2i=cn, data=dat)


# Now lets had study "XING", which has a MD of 8 (95%CI: 4, 12), n=60;
p=0.001

sampling variance = (CI / 1.96) ^ 2 / (2 * sample size)

(8 / 1.96) ^ 2 / (2 * 6) = 1.388


# Create a new row for study XING
new_row <- data.frame(study = "XING", en = NA, em = NA, esd = NA, cn = NA,
cm = NA, csd = NA, yi = 8, vi = 1.388)

# Add the new row to dat
dat <- rbind(dat, new_row)

#
res <- rma(yi, vi,  data=dat)
res
Michael Dewey
# 
Dear Jorge

I think the conv.wald() function in metafor will calculate the variance 
for you. You do need an up-to-date version of metafor.

Michael
On 26/03/2023 21:28, Jorge Teixeira via R-sig-meta-analysis wrote:

  
    
  


  


      

    

    

      
      

        


  

        

      Jorge Teixeira
    

    

      
      #
    

  


  

      
Dear Michael, thank you - that is indeed more elegant.

Out of curiosity, is it possible to do this in ?meta? package too?

Michael Dewey <lists at dewey.myzen.co.uk> escreveu no dia segunda, 27/03/2023
?(s) 13:32:

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        

  
  


  


      

    

    

      
      

        


  

        

      Dr. Gerta Rücker
    

    

      
      #
    

  


  

      
Dear Jorge,

First of all, your formula for the variance of the XING study does not seems correct to me. I would expect for the sampling variance:

SE^2 = (CI.length / 1.96 /2)^2 = (8 / 1.96 / 2)^2 = 4.164931

(It is correct that you don't need the sample size.)

This gives with metafor:
estimate      se    zval    pval    ci.lb   ci.ub    
  2.0751  1.0832  1.9156  0.0554  -0.0481  4.1982  .

Now how it works with meta:

# Your data
dat <- structure(list(study = c("AA", "BB", "CC", "EE", "DDD"), 
                      en = c(9, 41, 29, 8, 13), 
                      em = c(32, 27.5, 28.7, 22.8, 30.5), 
                      esd = c(1.9, 3.8, 5.2,  3.8, 4.9), 
                      cn = c(8, 26, 28, 10, 14), 
                      cm = c(30.1, 24.9, 26.9, 24.7, 30.2), 
                      csd = c(2.4, 3.6, 3, 4.3, 5.1)), 
                 row.names = c(NA,-5L), class = c("tbl_df", "tbl", "data.frame"))
# Meta-analysis of continuous data with metacont()
m0 <- metacont(n.e = en, mean.e = em, sd.e = esd, n.c = cn, mean.c = cm, sd.c = csd, 
               data = dat)
# Use treatment effects (TE) and their standard errors (seTE) from m0, add the CI of study XING and conduct generic inverse variance meta-analysis
# metagen() will do the transformation from CI to TE and seTE
m1 <- metagen(TE = c(m0$TE, NA), seTE = c(m0$seTE, NA),
              lower = c(NA, NA, NA, NA, NA, 4),
              upper = c(NA, NA, NA, NA, NA, 12),
              common = FALSE, method.tau = "REML")
m1
forest(m1)

Best,
Gerta






UNIVERSIT?TSKLINIKUM FREIBURG
Institute for Medical Biometry and Statistics

Dr. Gerta R?cker
Guest Scientist

Stefan-Meier-Stra?e 26 ? 79104 Freiburg
gerta.ruecker at uniklinik-freiburg.de

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


-----Urspr?ngliche Nachricht-----
Von: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org> Im Auftrag von Jorge Teixeira via R-sig-meta-analysis
Gesendet: Montag, 27. M?rz 2023 16:25
An: Michael Dewey <lists at dewey.myzen.co.uk>
Cc: Jorge Teixeira <jorgemmtteixeira at gmail.com>; R Special Interest Group for Meta-Analysis <r-sig-meta-analysis at r-project.org>
Betreff: Re: [R-meta] combining Means + SD at post, withD + 95% CI

 Dear Michael, thank you - that is indeed more elegant.

Out of curiosity, is it possible to do this in ?meta? package too?

Michael Dewey <lists at dewey.myzen.co.uk> escreveu no dia segunda, 27/03/2023
?(s) 13:32:

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        
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