Dear R-experts!

I am currently running a meta-analysis with the help of the great metafor
package. However I have some difficulties setting up my raw data to enter it
to the meta-analysis models.
I have a group of subjects that have been measured in two continuous
variables (A & B). I have the information about the mean of the two
variables, the group size (n) and the standard deviations of the two
variables.
Now I would like to average both variables (A & B) and get the mean and
standard deviation of the merged variable (C).
As for the mean this would be quiet easy: I would just take the mean of mean
A and mean B to get the mean of C.
However for the standard deviation this seems more tricky as it is to assume
that standard deviations in A & B correlate. I assume (based on further
analysis) a correlation of r =0.5.
I found the formula to get the standard deviation of the SUM (not the mean)
of two variables:
SD=SQRT(SD_A^2 + SD_B^2 + 2*r*SD_A*SD_B)

with SD_B and SD_B being the standard deviation of A and B. And r*SD_A*SD_B
being the covariance of A and B.

Would this formula also be valid if I want to average (and not sum) my two
variables?

Many thanks for any help & best wishes,
Jokel

        [[alternative HTML version deleted]]

______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Reply via email to