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st: RE: Using command svy glm to obtain risk ratios

From   "Hussein, Mustafa (Mustafa Hussien)" <>
To   "" <>
Subject   st: RE: Using command svy glm to obtain risk ratios
Date   Mon, 17 Feb 2014 16:32:35 +0000


I am not sure why your -svy- procedure won't give eform coefficients (RRs) with the log-binomial GLM (which you are trying to run here). A better alternative to log-binomial regression for estimating RRs (or prevalence rate ratios if cross-sectional data) is a modified Poisson (Poisson w robust SEs). The log-binomial is well-known to have issues with convergence and, as you've experienced, takes forever. A Poisson model is very easy to do using -glm- or -poisson-, and with pweighted-survey data, you've got to just add the eform option (or -, irr- with poisson).

Hope that helps
From: [] on behalf of Agunwamba, Amenah A., Ph.D. []
Sent: Monday, February 17, 2014 9:47 AM
Subject: st: Using command svy glm to obtain risk ratios

Hello Stata Experts,

I'm attempting to obtain risk ratios using weighted survey data. I'm using a binary outcome. For a simple model, I use the following code:

Svy: glm outcome predictor, fam(binomial) link(log) eform

Stata then does some "thinking.....", and takes forever to finally produce a table that has only coefficients and standard errors, but not the risk ratios that I am looking for. Is there something wrong with my data or my code? How would I assess if there' something wrong with the data (eg: convergence, etc?)

I believe I need to use the svy command to incorporate weighting. I was able to obtain risk ratios without the svy command, but I need to use weights. Any suggestions on different commands I could use to get the results I'm looking for?

Thanks in advance,

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