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Home » Data » Dataset use (other programs) » multilevel log-binomial regression (how do i estimate the risk ratio for a clustered binary out come using log binoial model.)
multilevel log-binomial regression [message #25263] Sun, 25 September 2022 01:31 Go to previous message
jessy is currently offline  jessy
Messages: 8
Registered: August 2022
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Dear all,
I am currently running my thesis, comparing the performance of binary logistic, modified Poisson and log binomial models in determining factors associated with teen pregnancies.

I am trying to fit a multilevel log-binomial model in order to calculate the prevalence (risk) ratio (rather than the odds ratio) for a clustered binary outcome and am running into an unexpected error.

using the glm command, one can correctly specify a single-level log-binomial model as

glm depvar indvar, family(binomial) link(log) eform

However, when specifying the same model as a 2 level-level, random intercept model using meglm

meglm depvar indvar || village: || household: , family(binomial) link(log) eform

I get the following error,

link log is not allowed with family bernoulli
r(198);

I am running Stata 14, so am wondering if there is an extra package i need to install to be able to run the log-binomial model at 2 levels.
or it is simply a limitation of the meglm command. Any insights or suggestions would be much appreciated

Thanks!!
 
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