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st: R: left censoring


From   "Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: R: left censoring
Date   Fri, 5 Dec 2008 15:01:00 +0100

Dear Ioanna,
tricky issue indeed.

Anyway, I would refer you to:

Cleves MA, Gould WW, Gutierrez RG. An introduction to survival analysis
using Stata. Revides Edition. Station College: Stata Press, 2004: 32-34;

Klein JP, Moeschberger ML. Survival Analysis. Techniques for Censored and
Truncated Data. Second Edition. Berlin: Springer, 2003: 70-71;74;140-141.

Sorry I cannot be more helpful.

Knd Regards,
Carlo
-----Messaggio originale-----
Da: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di IOANNA MARIOU
STYLIANOU
Inviato: giovedì 4 dicembre 2008 21.01
A: statalist@hsphsun2.harvard.edu
Oggetto: st: left censoring

Hi

iam trying to estimate duration models(Cox-PH) but i have left
censoring..Does anyone knows how this is treated in STATA?

Ioanna Stylianou

----- Original Message -----
From: Christopher Baum <baum@bc.edu>
Date: Thursday, December 4, 2008 1:54 pm
Subject: st: Re: how to select model in xtpcse , corr(ar1)
To: statalist@hsphsun2.harvard.edu


> < >
>  Ghislain said
>  I want to compare two models one made with : xtpcse x y z,corr(ar1)  
> 
>  the other with : xtpcse x y w,corr(ar1) xtpcse doesn't return AIC nor 
>  
>  BIC nor e(ll),
>  
>  Martin suggests looking at r^2.  AIC and BIC are criteria that will  
> 
>  penalize for non-parsimonious models. As both of the models you  
>  specify have exactly the same length, they would not be useful. They  
> 
>  are not estimated with maximum likelihood, so there is no e(ll). [OLS 
>  
>  is not estimated with MLE either, but -regress- does provide e(ll)].  
>  
>  As r^2 is perfectly comparable for models of the same length, r^2  
>  would seem to make sense as a comparison.
>  
>  I would worry more about the notion that if each of these models does 
>  
>  a good job, with a significant z or w respectively, then there is  
>  surely the risk that they are both misspecified versions of a model  
> 
>  that contains both. Can you indeed rule out w appearing in the first  
> 
>  model, or z in the second?
>  
>  
>  Kit Baum, Boston College Economics and DIW Berlin
>  http://ideas.repec.org/e/pba1.html
>  An Introduction to Modern Econometrics Using Stata:
>  http://www.stata-press.com/books/imeus.html
>  
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