Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Gwinyai Masukume <parturitions@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Interpretation of Two-sample t test with equal variances? |

Date |
Wed, 20 Mar 2013 18:16:26 +0200 |

Thank you so much everyone. Appreciated. David - it was indeed a very helpful discussion. Nick - indeed those are means of maternal age. you are significant. yes, the mother's ages are skewed. what do you mean by student's t test works well even if you lie to it? Carlo - it seems all the relevant independent variables have not been included, the very low pseudo r2 is bizarre to me. Thanks again. Gwinyai On 3/20/13, Carlo Lazzaro <carlo.lazzaro@tiscalinet.it> wrote: > Gwinyai, > your Pseudo R2 = 0.0015 seems very low. > Are you sure that all the relevant independent variables have been included > in your model? > > You may also consider searching for interactions between mode_delivery & > age. > > Best regards, > Carlo > > -----Messaggio originale----- > Da: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Gwinyai Masukume > Inviato: mercoledì 20 marzo 2013 06:05 > A: statalist@hsphsun2.harvard.edu > Oggetto: Re: st: Interpretation of Two-sample t test with equal variances? > > Thank you Richard. Yes, I guess the t-test suggests the counter intuitive > though it probably won’t change things much. > How can I reverse the situation? > > I ran a logistic regression for binary outcomes as you suggested: > Essentially no significance is shown? > > . logit mode_delivery age > > Iteration 0: log likelihood = -159.58665 > Iteration 1: log likelihood = -159.34203 > Iteration 2: log likelihood = -159.34197 > Iteration 3: log likelihood = -159.34197 > > Logistic regression Number of obs = > 250 > LR chi2(1) = > 0.49 > Prob > chi2 = > 0.4842 > Log likelihood = -159.34197 Pseudo R2 = > 0.0015 > > ---------------------------------------------------------------------------- > --- > mode_delivery | Coef. Std. Err. z P>|z| [95% Conf. > Interval] > --------------+--------------------------------------------------------- > --------------+------- > age | .0155454 .0222368 0.70 0.485 -.028038 > .0591288 > _cons | -1.133737 .6630978 -1.71 0.087 -2.433385 > .1659111 > ---------------------------------------------------------------------------- > --- > > With thanks, > Gwinyai > > On 3/20/13, Richard Williams <richardwilliams.ndu@gmail.com> wrote: >> Your t-test seems to suggest that age is affected by mode of delivery, >> rather than mode of delivery is affected by age. It probably won't >> change things much but this makes more sense to me given your >> hypotheses: >> >> logit mode_delivery age >> >> At 11:08 PM 3/19/2013, Gwinyai Masukume wrote: >>>Dear Stata list, >>> >>>I would like to double check the interpretation and appropriateness of >>>the following statistical test I performed. >>>My alternate hypothesis is that, “There is a difference in the baby’s >>>mode of delivery depending on maternal age” And the null hypothesis is >>>that, “There is no difference in the baby’s mode of delivery depending >>>on maternal age” >>>Looking at the output “Ha: diff != 0, Pr(|T| > |t|) = 0.4861”, I >>>fail to reject the null hypothesis and conclude that, “There is no >>>difference in the baby’s mode of delivery depending on maternal age” >>> >>>Is this a sound and appropriate interpretation? >>> >>>. *** Doing a T-test >>>. ttest age, by(mode_delivery) >>> >>>Two-sample t test with equal variances >>>-------------------------------------------------------------------------- > ---- >>> Group | Obs Mean Std. >>> Err. Std. Dev. [95% Conf. Interval] >>>---------+------------------------------------------------------------ >>>---------+-------- >>> Vaginal >>> | 166 28.83072 .4696729 6.051313 27.90338 29.75807 >>>C/sectio | 84 29.39524 .6579862 6.030543 28.08653 >>> 30.70395 >>>---------+------------------------------------------------------------ >>>---------+-------- >>>combined | 250 29.0204 .3818851 6.038134 28.26826 >>> 29.77254 >>>---------+------------------------------------------------------------ >>>---------+-------- >>> diff >>> | -.5645152 .8093331 -2.158558 1.029528 >>>-------------------------------------------------------------------------- > ---- >>> diff = mean(Vaginal) - >>> mean(C/sectio) t = -0.6975 >>>Ho: diff = 0 degrees of freedom = >>> 248 >>> >>> Ha: diff < 0 Ha: diff != 0 Ha: diff >>> > >>> 0 >>> Pr(T < t) = 0.2431 Pr(|T| > |t|) = >>> 0.4861 Pr(T > t) = 0.7569 >>> >>>With kind regards, >>>Gwinyai >>> >>>* >>>* For searches and help try: >>>* http://www.stata.com/help.cgi?search >>>* http://www.stata.com/support/faqs/resources/statalist-faq/ >>>* http://www.ats.ucla.edu/stat/stata/ >> >> ------------------------------------------- >> 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/faqs/resources/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/faqs/resources/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/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Interpretation of Two-sample t test with equal variances?***From:*David Hoaglin <dchoaglin@gmail.com>

**Re: st: Interpretation of Two-sample t test with equal variances?***From:*Nick Cox <njcoxstata@gmail.com>

**References**:**st: Interpretation of Two-sample t test with equal variances?***From:*Gwinyai Masukume <parturitions@gmail.com>

**Re: st: Interpretation of Two-sample t test with equal variances?***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**Re: st: Interpretation of Two-sample t test with equal variances?***From:*Gwinyai Masukume <parturitions@gmail.com>

**R: st: Interpretation of Two-sample t test with equal variances?***From:*"Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it>

- Prev by Date:
**Re: st: Modelling Relative Risks with -fracpoly-** - Next by Date:
**st: STATA command equivalent to SPSS "aggregate"?** - Previous by thread:
**R: st: Interpretation of Two-sample t test with equal variances?** - Next by thread:
**Re: st: Interpretation of Two-sample t test with equal variances?** - Index(es):