Dear STATALIST,

I am writing you as I am having some STATA issues regarding probably simple commands I cannot find.

For a systematic review, as some of the studies do not explicitly report all data necessary for a meta-analysis, I am attempting to generate the estimates needed, with the little data provided. For a meta analysis, if a study provides the count data (i.e. value of n (observations) and value of N (total number of observations) per treatment group), the risk ratio (rr), log risk ratio (logrr), standard error of log risk ratio (selogrr), and lower (lcirr) and upper confidence (ucirr) interval limits around the log risk ratio can be computed with the following commands:

//Generate risk ratio
gen rr2= (n1/N1)/(n2/N2)

//Generate ln(RR)
gen logrr2=log(rr2)

//Generate variance of ln(RR)
gen varlogrr2=1/n1-1/N1+1/n2-1/N2


//Generate SE of ln(RR)
gen selogrr2=((varlogrr2)^(1/2))*1.22


//Generate lower limit 95%ci of RR
gen lcirr2=(log(rr2)-1.96*selogrr2)


//Generate upper limit 95%ci of RR
gen ucirr2=(log(rr2)+1.96*selogrr2)

Some studies only provide the proportions with the corresponding p-value, and no other information. However, this is sufficient to at least compute the risk ratio, log of the risk ratio, get the z-score (from the p-value) and thus compute the standard error.

I however do not know what command to use to then compute the log of the standard error, which as per the command above, I would need to be able to compute the confidence intervals around the log risk ratio. The variance would usually be used to compute the standard error, with 1.22 as a multiplier to account for clustering. However, I would need count data to be able to compute the variance.

I was thus wondering if STATA had commands that would allow me to compute the log of the standard error, without having to use the variance of the log risk ratio?

Here is a dataset containing the data I could compute based on the little information provided.


Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input float(RR logrr p1 p0 pv z)
4.75 1.5581446 .19 .04 .18 1.34
end
​​​​​​​

Thank you very much.