Thank you all for your feedback.
I have individual-level data from the US on whether a child has been
diagnosed with ADHD (attention deficit/hyperactivity disorder). The data is
from a complex survey design where each child has a probability of selection
weight and each stratum is a state, so state-level estimates are valid.
My research question--better stated from Steve Samuel's suggestion--:
First null hypothesis structure:
Ho: proportion of US's children with ADHD minus proportion of state's (e.g.,
Michigan's) children with ADHD = 0
Using my sample, I wanted to use a statistical test to determine whether or
not to reject the null hypothesis, where there would be 50 null hypotheses
(one for each state). Michael Frone's Tuesday, December 05, 2006 8:27 AM
(PST) email provides a method for this. (Need to further investigate Austin
Nichols's reply.)
The second null hypothesis structure is:
Ho: proportion of e.g., non-Michigan's children with ADHD minus proportion
of e.g., Michigan's children with ADHD = 0; As above, there would be 50 null
hypotheses (one for each state).
There are many methods to test this null hypothesis in Stata. From a
practical standpoint, the decision whether to reject the null hypothesis
using the first null hypothesis structure for a particular state will likely
be the same as the decision for the second null hypothesis structure.
I then plan to use an indirect-adjustment method to adjust the states' ADHD
prevalence rates for different child-level characteristics across states,
and re-run the hypotheses tests with the adjusted rates.
Your input has provided me methods for the first null hypothesis
structure--which I didn't have before. And since the scope of this
issue--which null hypothesis structure is typically used in the literature
and the strengths/weaknesses of each--is getting beyond Stata usage, I don't
want to burden this email list. After thinking about it more, I think the
second null hypothesis structure is cleaner since I can come up with
examples that would make the first structure answer a very odd question.
Maybe the literature (that I have read) that states they are using the first
structure are, in fact, actually using the second? But if you have
suggestions for me personally, I'd welcome them.
Thanks,
Brent
-----Original Message-----
From: [email protected]
[mailto:[email protected]]On Behalf Of Steven Samuels
Sent: Tuesday, December 05, 2006 4:45 PM
To: [email protected]
Subject: Re: st: statistical test to compare two survey means from two
estimating equations
On Dec 5, 2006, at 4:06 PM, Nick Cox wrote:
> I'm still puzzled by the over-arching question and curious
> as to how this fits into any research project.
Nick, I couldn't agree more. In the days when I did walk-in
consulting for faculty and students, I never started out by answering
a researcher's
question. Usually I asked "What's the problem? Why do you want to do
this?" More often then not, the researcher hadn't really thought out
his project. My biggest contribution was helping to define the
research problem, and the original question was irrelevant.
In the list we usually answer the question first and don't always
think to ask if it's the right one. It's inevitable perhaps, given
the nature of the list, but unfortunate.
Steve
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