# Re: st: predict cs, csnell: missings

 From Ricardo Ovaldia To statalist@hsphsun2.harvard.edu Subject Re: st: predict cs, csnell: missings Date Mon, 14 Feb 2005 05:33:50 -0800 (PST)

```--- Verena Schoenleber
<verena.schoenleber@uni-konstanz.de> 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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