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From |
Bert Jung <bjung59@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: -ttest- or -prtest-? |

Date |
Sun, 26 Apr 2009 22:34:42 -0400 |

Thanks Richard, much appreciated. Here an example code to play with; the p-values are very close in most cases I tried. Bert * Comparing -ttest-, -prtest- and -logit- for binary outcomes clear set obs 100 * Proportion of sample set to y = 1 in each of group 0, 1 scalar r1 = 0.4 scalar r2 = 0.5 * Two groups (x = 0, 1) with equal number of obs gen x = 1 if _n<=_N/2 recode x (.=0) gen y = 0 replace y = 1 if x==1 & _n <= r1* (_N/2) replace y = 1 if x==0 & _n > _N - ( r2* (_N/2) ) tab y x, miss ttest y, by(x) prtest y, by(x) logit y x On Sat, Apr 25, 2009 at 12:15 AM, Richard Williams <Richard.A.Williams.5@nd.edu> wrote: > 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 > > > ------------------------------------------- > Richard Williams, Notre Dame Dept of Sociology > OFFICE: (574)631-6668, (574)631-6463 > HOME: (574)289-5227 > EMAIL: Richard.A.Williams.5@ND.Edu > WWW: http://www.nd.edu/~rwilliam > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: -ttest- or -prtest-?***From:*Bert Jung <bjung59@gmail.com>

**Re: st: -ttest- or -prtest-?***From:*Richard Williams <Richard.A.Williams.5@ND.edu>

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