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 |
"Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it> |

To |
<statalist@hsphsun2.harvard.edu> |

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

Date |
Wed, 20 Mar 2013 15:48:42 +0100 |

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/

**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:*Gwinyai Masukume <parturitions@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>

- Prev by Date:
**Re: st: Interpretation of Two-sample t test with equal variances?** - Next by Date:
**st: Modelling Relative Risks with -fracpoly-** - Previous by thread:
**Re: 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):