I want to perform a meta-analysis of survival estimates, and I want to fit a random effects model. I am working in
R, and my data.frame looks something along the lines of:
Study Age10 Age20 Age30 ... A 0.90 0.83 0.70 B 0.99 0.93 0.78 . . . . . . . . . . . .
I've been looking into the DerSimonian-Laird model and the function I came across in R only handles meta-analysis of odds ratios? What's an R function for handling survival estimates?
library("rmeta") data("smoking", package = "HSAUR") smokingDSL <- meta.DSL(smoking[["tt"]], smoking[["tc"]], smoking[["qt"]], smoking[["qc"]], names = rownames(smoking)) summary(smokingDSL)
Does it make sense to apply the DSL model to meta-analyze survival estimates? Or should I look into another random effects model? Also, is there a package in R that lets me fit the model?