thank you. i think that's the explanation!
verena
--
University of Konstanz
Germany
> Date: Mon, 14 Feb 2005 05:33:50 -0800 (PST)
> From: Ricardo Ovaldia <[email protected]>
> Subject: Re: st: predict cs, csnell: missings
>
> - --- Verena Schoenleber
> <[email protected]> wrote:
>
> > i am trying to test the overall model fit of my cox
> > model, using
> > cox-snell residuals.
>
> > the command predict cs, csnell
> > seems to work, but it generates a large amount of
> > missings.
> >
> > can anyone explain me what is going on? what can i
> > do solve the
> > problem?
>
> - -predict, csnell- will only compute the residual for
> observations without missing data. For example:
>
> . sysuse auto, clear
> (1978 Automobile Data)
>
> . stset mpg foreign
>
> failure event: foreign != 0 & foreign < .
> obs. time interval: (0, mpg]
> exit on or before: failure
>
> -
>
------------------------------------------------------------------------------
> 74 total obs.
> 0 exclusions
> -
>
------------------------------------------------------------------------------
> 74 obs. remaining, representing
> 22 failures in single record/single failure
> data
> 1576 total analysis time at risk, at risk from t
> = 0
> earliest observed entry t
> = 0
> last observed exit t
> = 41
>
> . stcox rep78 price, mgale(mg)
>
> failure _d: foreign
> analysis time _t: mpg
>
> Iteration 0: log likelihood = -57.493118
> Iteration 1: log likelihood = -53.497231
> Iteration 2: log likelihood = -53.220366
> Iteration 3: log likelihood = -53.218995
> Iteration 4: log likelihood = -53.218995
> Refining estimates:
> Iteration 0: log likelihood = -53.218995
>
> Cox regression -- Breslow method for ties
>
> No. of subjects = 69
> Number of obs = 69
> No. of failures = 21
> Time at risk = 1469
> LR
> chi2(2) = 8.55
> Log likelihood = -53.218995
> Prob > chi2 = 0.0139
>
> -
>
------------------------------------------------------------------------------
> _t | Haz. Ratio Std. Err. z P>|z|
> [95% Conf. Interval]
> -
>
-------------+----------------------------------------------------------------
> rep78 | 1.342636 .4218106 0.94 0.348
> .7253372 2.485289
> price | 1.000263 .0000816 3.22 0.001
> 1.000103 1.000423
> -
>
> . predict cs, csnell
> (5 missing values generated)
>
> There are 5 observation that have missing rep78
> values, therefore there are 5 missing residuals.
>
> Hope this helps,
> Ricardo.
>
> =====
> Ricardo Ovaldia, MS
> Statistician
> Oklahoma City, OK
>
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