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

 From "Carlo Lazzaro" To 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

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
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>
>
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