Re: Stcox ereturn list: wrong chi2 p-value?s

["Martin Weiss" <martin.weiss1@gmx.de>]

I would not know how to do this with -outreg2-, but if you could be bothered 
to use the -estout- family of commands, then

********
clear*
cap ssc inst estout
webuse stan3, clear
stset
stcox age posttran surg yea
estadd sca prchi2= 1-chi2(e(df_m),e(chi2))
eststo
esttab, sca(prchi2)
********

Tweak the -esttab- line to your needs, i.e. Latex output or csv... See -h 
esttab-

HTH
Martin
_______________________
----- Original Message ----- 
From: "junin" <dv.junin@gmail.com>
To: <statalist@hsphsun2.harvard.edu>
Sent: Sunday, September 21, 2008 11:52 AM
Subject: Stcox ereturn list: wrong chi2 p-value?s



> Hello,
>
> I have a question concerning the output of a Cox regression, which I
> want to access with outreg2. Below you find the results of the Cox
> regression command as well as the ereturn list results. My question
> is: Why doesn't the  e(r2_p) =  .0006402283288656 repor the  Prob >
> chi2     =    0.0025?
> How can I access the Prob > chi2?
>
> Thank you for you help,
>
> dirk
>
>
> Cox regression -- Breslow method for ties
>
> No. of subjects =         1970                     Number of obs   = 
> 15654
> No. of failures =         1065
> Time at risk    =        15654
>                                                  LR chi2(1)      = 
> 9.17
> Log likelihood  =   -7153.7882                     Prob > chi2     = 
> 0.0025
>
> ------------------------------------------------------------------------------
>         _t | Haz. Ratio   Std. Err.      z    P>|z|     [95% Conf. 
> Interval]
> -------------+----------------------------------------------------------------
>     Xsales |     .99992   .0000413    -1.94   0.053     .9998391 
> 1.000001
> ------------------------------------------------------------------------------
>
> . ereturn list
>
> scalars:
>                 e(N) =  15654
>              e(ll_0) =  -7158.37122089778
>                e(ll) =  -7153.788228853626
>              e(df_m) =  1
>              e(chi2) =  9.165984088309415
>              e(r2_p) =  .0006402283288656
>             e(N_sub) =  1970
>            e(N_fail) =  1065
>              e(risk) =  15654
> *
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