I am examining the association between binge drinking and neighborhood
poverty using survey data. Because binge drinking is highly prevalent
I
would like to use glm to estimates relative risks (instead of logistic
regression
& odds ratios).
Past year binge drinking is categorized into 3 groups: no binge
(referent); binge <1 month; and binge ≥1 month. In one glm model, I
compare binge <1 month (binge2lt) to no binge drinking. In a separate
glm model, I compare binge ≥1 month (binge2gt) to no binge drinking.
I want to evaluate whether the risk of binge drinking associated with
neighborhood poverty is different for men and women (e.g. does sex
modify the relation between binge drinking and neighborhood poverty?).
I
am new to the suest command and am not sure I am using properly. Can I
use the suest command to combine the two separate models and test the
interaction jointly across binge drinking categories?
Below is some example code of what I’m trying to do. Is this
correct?
Thanks in advance for any assistance! -Christy
EXAMPLE CODE:
xi: svy: glm binge2lt poverty sex i.sex*poverty, fam(poisson)
link(log)
nolog eform
est store b1
xi: svy: glm binge2gt poverty sex i.sex*poverty, fam(poisson)
link(log)
nolog eform
est store b1a
suest b1 b1a
test [b1_binge2lt]_IsexXpover_1 [b1a_binge2gt]_IsexXpover_1
Christy McKinney, PhD, MPH
Faculty Associate, Epidemiology
UT Houston School of Public Health
Dallas Regional Campus
6011 Harry Hines Blvd., V8.106
Dallas, TX 75390-9128
[email protected]
(214)648-6574 (phone)
(214)648-1081 (fax)
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