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

 From Gwinyai Masukume 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
>
> 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
>>>
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>>
>> -------------------------------------------
>> 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
>>
>>
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```