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


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 20:06:55 +0100

I agree with Nick.
For instance, other things being equal, the way nulliparous deliver may be influenced by the reimbursement the hospital gets by the health care system for a given delivery procedure.
Other issue such as adherence on clinical guide-lines (and to what extent) or physicians' fear of being charged of malpractice may also play a role, as far as I am concerned. 
Some other independent variables, that I recall from my strolling around literature and interviewing, might deserve consideration: patients' smoking status; Body Mass Index; diabetes; hypertension; eclampsia; gestosis; risky pregnancy; patients' diseases that may urge gynecologist to prefer C/section; evidence low birth weight; abnormalities in fetal heart rate.
As a general remark, I am still under the impression that readers will find a single predictor logistic regression model quite weak in this instance.

Hope this may contribute to ease the way.

Kind regards,
Carlo
-----Messaggio originale-----
Da: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Nick Cox
Inviato: mercoledì 20 marzo 2013 19:29
A: statalist@hsphsun2.harvard.edu
Oggetto: Re: st: Interpretation of Two-sample t test with equal variances?

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.

Nick

On Wed, Mar 20, 2013 at 6:17 PM, Gwinyai Masukume <parturitions@gmail.com> 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 <carlo.lazzaro@tiscalinet.it> 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: owner-statalist@hsphsun2.harvard.edu
>> [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di David 
>> Hoaglin
>> Inviato: mercoledě 20 marzo 2013 17:33
>> A: statalist@hsphsun2.harvard.edu
>> 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 
>> <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.

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