metaprop from stata to R

[antoine4ucsd]

Hello,

I need to do some meta-analyses in R (moving away from stata that was used by previous collaborators) My problem is that I cannot reproduce the results….

For example The data was: Study case pop Study1 5 119 Study2 116 170 And then in stata: Metaprop case pop, random

I get this: 0.18 (95%CI 0.14-0.21)

But in R I tried many combinations… events=c(5,116) n=c(119,170)

meta_data <- metaprop(event,n,method="GLMM", comb.fixed = FALSE) forest(meta_data) meta_data proportion 95%-CI 1 0.0420 [0.0138; 0.0953] 2 0.6824 [0.6067; 0.7515]

Number of studies combined: k = 2

Random effects model 0.2355 [0.0191; 0.8297]

Details on meta-analytical method:

• Random intercept logistic regression model
• Maximum-likelihood estimator for tau^2
• Logit transformation

• Clopper-Pearson confidence interval for individual studies

  I also tried various other approaches. The closest results I obtained was with the following. It gives me good point estimates but not confidence intervals… I also tried woth double arcsine transformation (sm=”PFT”) but no luck… meta_data3 <- metaprop(events,n,method="inverse",sm = "PLN", comb.fixed = F,overall=T,method.tau="REML",method.tau.ci="BJ") proportion 95%-CI %W(random) 1 0.0420 [0.0138; 0.0953] 48.8 2 0.6824 [0.6067; 0.7515] 51.2

Number of studies combined: k = 2

Random effects model 0.1752 [0.0114; 1.0000]

Details on meta-analytical method:

• Inverse variance method
• Restricted maximum-likelihood estimator for tau^2
• Log transformation
• Clopper-Pearson confidence interval for individual studies

Do you know how to reproduce stata ‘metaprop random function’ in R (default parameters)???

2 Second (hopefully easier) question:

how can I extract the 95%CI of random effect models from the meta results???

thank you!

[guido-s]

Hi,

I cannot explain the different results, however, the random effects CI calculated in Stata seems to be much too small. The two proportions are very different and the confidence intervals are far apart. Furthermore, I2 is above 90%. All this is not reflected in the RE CI from 0.14 to 0.21.

Concerning your second questions. The transformed random effects CI limits are stored in list elements lower.random and upper.random.

ev <- c(5, 116)
N <- c(119, 170)

m <- metaprop(ev, N)
summary(m)
m$lower.random
meta:::logit2p(m$lower.random)

m.pas <- metaprop(ev, N, sm = "PAS")
summary(m.pas)
meta:::asin2p(m.pas$lower.random)
meta:::asin2p(m.pas$upper.random)

m.pft <-  metaprop(ev, N, sm = "PFT")
summary(m.pft)
1 / mean(1 / N) # harmonic mean
meta:::asin2p(m.pft$lower.random, 1 / mean(1 / N))
meta:::asin2p(m.pft$upper.random, 1 / mean(1 / N))