Hi,
I am using Stata 9.2 and wanted to test whether the parameter estimate for
the variable "hispanic" was statistically different in model 1 as compared
to model 2. I assume that -suest- followed by -test- is the appropriate
procedure, but it is giving me puzzling results. How is it possible when the
estimates only differ by 0.017 that the p-value of the Wald test is
remarkably low at 0.0991? It must be the case that the standard error of the
0.017 statistic is very low, but I'm not sure how that's possible given that
the standard errors of the parameter estimates in both models were 0.347.
I'd appreciate your advice.
code:
svy, subpop(if sample1==1): logit adhd_d $ind1a `geodummies'
estimates store m1a
svy, subpop(if sample1==1): logit adhd_d $ind1b `geodummies'
estimates store m1b
suest m1a m1b, svy
test [m1a]hispanic=[m1b]hispanic
output:
m1a--hispanic parameter, (se), (p-value): -0.310 (0.347) (0.372)
m1b--hispanic parameter, (se), (p-value): -0.327 (0.347) (0.346)
Adjusted Wald test (testing equality of hispanic parameter estimates)
F( 1, 78762) = 2.72
Prob > F = 0.0991
Thanks,
Brent Fulton
p.s. note that is a similar question to the link below, but no answer was
posted
http://www.stata.com/statalist/archive/2007-10/msg00870.html
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