Hi there
I just wanted to understand more about interpreting the random effects section of a multilevel model below:
------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
usualgpsor~e: Identity |
sd(_cons) | .1897804 .0254148 .1459692 .2467411
------------------------------------------------------------------------------
LR test vs. logistic model: chibar2(01) = 36.02 Prob >= chibar2 = 0.0000
I am looking at statin prescribing (the probability of), including several a priori predictors and have clustered by practice level (usualgpsor~e). How can I tell that including practice level in the model has helped to explain some of the variation.
And in this scenario how do I present this part of the output in a table. Happy to give more context to this if required.
Look forward to hearing from any STATA gurus
Thanks
Vian
I just wanted to understand more about interpreting the random effects section of a multilevel model below:
------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
usualgpsor~e: Identity |
sd(_cons) | .1897804 .0254148 .1459692 .2467411
------------------------------------------------------------------------------
LR test vs. logistic model: chibar2(01) = 36.02 Prob >= chibar2 = 0.0000
I am looking at statin prescribing (the probability of), including several a priori predictors and have clustered by practice level (usualgpsor~e). How can I tell that including practice level in the model has helped to explain some of the variation.
And in this scenario how do I present this part of the output in a table. Happy to give more context to this if required.
Look forward to hearing from any STATA gurus

Thanks
Vian
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