# Meta Analysis of Cox Regression Coefficients?

I'm looking for a bit of guidance on this, as my stats skills are leaving me treating this as a bit more black-boxish than I'm comfortable with.

So I have several datasets where I am employing Cox Regression on survival data and some molecular measurements. I'm using the coxph routine in R from the Survival analysis package. From this, I get a Beta coefficient, standard error, a z-score, p-value, etc.

All of that I'm comfortable with.

What I'd like to do is a meta-analysis over these coefficients from the different datasets. I've been using the Metafor package in R to do this. As input, I've been giving it the beta coefficients and associated standard errors output by the coxph routine.

I'm not entirely sure that the standard errors provided by the coxph are the variances I need to do the meta analysis, or whether I should be using some weighting scheme that take the size of each dataset (number of samples) into effect more explicitly. (e.g. I may have 40 samples in one data set and 700 in another)

thanks for any guidance

Just supply the beta coefficients and corresponding standard errors to the rma() function. So, your syntax should be like this:
rma(coef, sei=se, data=dat)

where coef is the name of the variable in dataset dat denoting the coefficients and se is the name of the variable for the corresponding standard errors. The standard errors already include the information about the number of samples (and actually, it's the number of "events", not the sample sizes, that determine the size of the standard errors).