Re: st: suest across two svy:glm models to test interaction

[Steven Samuels <sjhsamuels@earthlink.net>]

Christy-


Your -svy- statements are not correct:  binge2lt = 0 for those who  
binge � 1 month, and so includes those people in the reference group;  
similarly,  binge2gt will include those the <1 month people in the  
reference group.  You need -subpop- to include only the two groups in  
which you are interested.

Like, Maarten  I think that -suest- is a bad idea. I too think that  
your "common outcome" logic for  using the RR model is faulty. But I  
would go further: with common outcomes, main effects, as well as  
interactions, are hard to interpret, on the OR scale and the RR  
scale. I strongly suggest that you convert to the probability scale  
to have understandable results. That will not be easy to do with - 
suest-, for there is no need for the two "unrelated" equations to be  
compatible (i.e. to lead to three probabilities that sum to 1.

Another difficulty: with a Poisson family assumption, your relative  
risk models can easily lead to estimated probabilities, or their CI  
upper-endpoints, which are >1.   A command that fits the  
probabilities for all three outcomes is much better. Before running  
one of the ordered logit commands, as Maarten suggests, try -svy:  
mlogit-.  After these commands, run -mfx- or -margeff- (download from  
SSC) to show estimated effects on the probability scale.

-Steve

On Sep 8, 2008, at 5:20 PM, Christy McKinney wrote:


> 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
> christy.mckinney@utsouthwestern.edu
> (214)648-6574 (phone)
> (214)648-1081 (fax)
>
>
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