At 10:04 PM 4/24/2009, Bert Jung wrote:
Dear Statalisters,
I have an embarrassingly basic question: I am looking at a binary
variable, 0 for "no response" and 1 for "response". I want to compare
2 groups (treatment/control, also binary). In this situation is a
-ttest- appropriate or does it have to be a test of proportions
-prtest-?
My vague memory of stats 101 suggests to use -prtest- since the
dependent variable is categorical. But I can interpret my variable as
numerical. My understanding is that with many numerical categories a
t-test may be ok. But here the outcome is 0 or 1 and clearly limited
in that range, which calls for a -prtest-. The two tests would be
quite different in this case, so the choice matters. Any comments and
views much appreciated.
Use prtest. See the last page of
http://www.nd.edu/~rwilliam/stats1/TwoSample-Stata.pdf
In practice, though, it may not matter if you use a t-test instead,
at least if the samples are large.
The above is basically a "how to." For more of an explanation, see
the last few pages of
http://www.nd.edu/~rwilliam/stats1/x42.pdf
Note too that you could also set this up as a 2 by 2 table and do a
chi-square test of the model of independence. You can also then use
Fisher's exact test, which could be handy if the sample is
small. See pp. 4-7 of
http://www.nd.edu/~rwilliam/stats1/Categorical-Stata.pdf
Yet another strategy is to do logistic regression, e.g.
logit y x
As add-on: how can I obtain chi2 values for the proportional test when
using complex survey data?
I'm not sure you ever even get chi-square stats when using survey
data - you usually get F values or t values, I believe. The first
thing that leaps to mind is to do logistic regression, e.g.
svy: logit y x
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Richard Williams, Notre Dame Dept of Sociology
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