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

From   Nick Cox <>
Subject   Re: st: Interpretation of Two-sample t test with equal variances?
Date   Wed, 20 Mar 2013 18:29:01 +0000

What drives the decision on delivery mode any way? How far is it
clinician's choice, patient's choice? Do you have data on the patient
or clinician variables that influence or determine tha decision? If
you don't have all the predictors -- and it would be surprising if you
did -- there will be lots of unexplained variability.


On Wed, Mar 20, 2013 at 6:17 PM, Gwinyai Masukume
<> wrote:
> Hi again. Thanks, I'm learning a lot. Carlo - I'm developing a model
> to simulate nulliparous (first time) mothers. As you note, the
> C/section rate is about 30 percent. My model so far has few variables.
> It's very very hard simulating reality I'm discovering.
> With respect,
> Gwinyai
> On 3/20/13, Carlo Lazzaro <> wrote:
>> Dave is right.
>> Actually I have read Gwinyai's post too fast and suggested something wrong.
>> I am currently engaged in a project concerning pre-term delivery as
>> dependent variable, that I have mistaken as Gwinyai's y, too.
>> Anyway, provided that this is not a homework or an exercise on logistic
>> regression, I confirm my concerns about the limited number of predictors in
>> Gwinyai's model.
>> For instance, are all the women included in the model at their first
>> delivery?
>> Best regards,
>> Carlo
>> -----Messaggio originale-----
>> Da:
>> [] Per conto di David Hoaglin
>> Inviato: mercoledě 20 marzo 2013 17:33
>> A:
>> Oggetto: Re: st: Interpretation of Two-sample t test with equal variances?
>> Carlo,
>> What meaning do you assign to an interaction between mode_delivery (the
>> outcome variable) and age (the predictor)?
>> David Hoaglin
>> On Wed, Mar 20, 2013 at 10:48 AM, Carlo Lazzaro
>> <> 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.

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