[R-meta] metafor::escalc question: Confidence intervals for differences in standardized mean change -

[Dale Steele]

I'm following the example on the metafor website for Computing the
Difference in the Standardized Mean Change
<https://www.metafor-project.org/doku.php/analyses:morris2008>

I'd like to calculate a confidence interval for each of the
differences in the 'dat' dataframe, rather than calculating by hand as
I have attempted below.  As illustrated below,  I tried to convert
'dat' back to an 'escalc' object with:
new_dat <- escalc(measure = "GEN", dat, append = TRUE) with the hope
that summary(new_dat) would generate the desired confidence intervals,
but this failed with a "Error in as.vector(vi) : argument "vi" is
missing, with no default" error.

Is what I'm doing possible?.

Thanks!


Example below:

datT <- data.frame(
  m_pre   = c(30.6, 23.5, 0.5, 53.4, 35.6),
  m_post  = c(38.5, 26.8, 0.7, 75.9, 36.0),
  sd_pre  = c(15.0, 3.1, 0.1, 14.5, 4.7),
  sd_post = c(11.6, 4.1, 0.1, 4.4, 4.6),
  ni      = c(20, 50, 9, 10, 14),
  ri      = c(0.47, 0.64, 0.77, 0.89, 0.44))

datC <- data.frame(
  m_pre   = c(23.1, 24.9, 0.6, 55.7, 34.8),
  m_post  = c(19.7, 25.3, 0.6, 60.7, 33.4),
  sd_pre  = c(13.8, 4.1, 0.2, 17.3, 3.1),
  sd_post = c(14.8, 3.3, 0.2, 17.9, 6.9),
  ni      = c(20, 42, 9, 11, 14),
  ri      = c(0.47, 0.64, 0.77, 0.89, 0.44))

datT <- escalc(measure="SMCR", m1i=m_post, m2i=m_pre, sd1i=sd_pre,
ni=ni, ri=ri, data=datT)
datC <- escalc(measure="SMCR", m1i=m_post, m2i=m_pre, sd1i=sd_pre,
ni=ni, ri=ri, data=datC)

summary(datT) #generates CI's for within-arm standardized differences
summary(datC)

dat <- data.frame(yi = datT$yi - datC$yi, vi = datT$vi + datC$vi)
# dat is no longer an 'escalc' object
# Next line fails with error
new_dat <- escalc(measure = "GEN", dat, append = TRUE)
dat$sei <- sqrt(dat$vi)
dat$zi <- dat$yi/dat$sei
dat$ci_lb <- dat$yi - dat$zi *dat$sei
dat$ci_ub <- dat$yi + dat$zi *dat$sei