Brent Fulton --
I think the last option is the best:
svy: tab y Michigan_dummy, col se
(the col and se options are important), after which you can
gen p21=.
gen p22=.
mat li e(b)
test p21=p22
Note that the concept of the mean for Michigan being different from
the national mean should rightly be reframed as the the mean for
Michigan being different from the mean for the balance of the nation,
as this reductio ad absurdum will illustrate: think of a sample of 3
people and compare the mean of the balance of the nation to the
national mean (e.g. are all people not named Brent Fulton
significantly more likely to have high blood pressure than the average
American?).
Also note that if you have categorical data, you want to estimate
proportions, not means, and the fact that the mean of a dummy variable
is a proportion does not mean that statistical tests using -svy: mean-
or -svy: reg- are appropriate for categorical dependent variables.
On 12/4/06, Brent Fulton <[email protected]> wrote:
I'm using Stata 9.2 and my dataset includes a complex survey design with
pweights and strata IDs, which are states. I have individual-level
observations within each state and want to perform a simple statistical
test: does the national mean of variable y equal the state of e.g.,
Michigan's mean of y, where y is 0/1.
I've run the following and can examine if the e.g., 95% CI's overlap, but
would like to calculate the p-value that the means are equal.
.svy: mean y
.svy: mean y, subpop(Michigan_dummy)
Is there a post-estimation test that can compare the survey-based means
above?
I've also thought of the following, but both compare Michigan to
non-Michigan states (not the nation).
.svy: logit y Michigan_dummy
.svy: tab y Michigan_dummy
Thanks,
Brent
___________________________________
Brent D. Fulton, PhD
Health Services Researcher
Petris Center at UC Berkeley
Phone: 510-643-4102
Fax: 510-643-4281
Email: [email protected]
www.petris.org
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