[R] calculating martingale residual on new data using "predict.coxph"

[David Winsemius]

On Nov 19, 2010, at 12:50 PM, David Winsemius wrote:

>
> On Nov 19, 2010, at 12:32 PM, Shi, Tao wrote:
>
>> Hi list,
>>
>> I was trying to use "predict.coxph" to calculate martingale  
>> residuals on a test
>> data, however, as pointed out before
>
> What about resid(fit) ?  It's my reading of Therneau & Gramsch [and  
> of help(coxph.object) ] that they consider those martingale residuals.

The manner in which I _thought_ this would work was to insert some  
dummy cases into the original data and then to get residuals by  
weighting the cases appropriately. That doesn't seem to be as  
successful as I imagined:

 > test1 <- list(time=c(4,3,1,1,2,2,3,3), weights=c(rep(1,7), 0),
+               status=c(1,1,1,0,1,1,0,1),
+               x=c(0,2,1,1,1,0,0,1),
+               sex=c(0,0,0,0,1,1,1,1))
 > coxph(Surv(time, status) ~ x , test1, weights=weights)$weights
Error in fitter(X, Y, strats, offset, init, control, weights =  
weights,  :
   Invalid weights, must be >0
# OK then make it a small number
 > test1 <- list(time=c(4,3,1,1,2,2,3,3), weights=c(rep(1,7), 0.01),
+               status=c(1,1,1,0,1,1,0,1),
+               x=c(0,2,1,1,1,0,0,1),
+               sex=c(0,0,0,0,1,1,1,1))
 > print(resid( coxph(Surv(time, status) ~ x ,  
test1,weights=weights) ) ,digits=3)
       1       2       3       4       5       6       7       8
-0.6410 -0.5889  0.8456 -0.1544  0.4862  0.6931 -0.6410  0.0509
Now take out constructed case and weights

 > test1 <- list(time=c(4,3,1,1,2,2,3),
+               status=c(1,1,1,0,1,1,0),
+               x=c(0,2,1,1,1,0,0),
+               sex=c(0,0,0,0,1,1,1))
 > print(resid( coxph(Surv(time, status) ~ x , test1) ) ,digits=3)
      1      2      3      4      5      6      7
-0.632 -0.589  0.846 -0.154  0.486  0.676 -0.632

Expecting approximately the same residuals for first 7 cases but not  
really getting it. There must be something about weights in coxph that  
I don't understand, unless a one-hundreth of a case gets "up indexed"  
inside the machinery of coxph?

Still think that inserting a single constructed case into a real  
dataset of sufficient size ought to be able to yield some sort of  
estimate, and only be a minor perturbation,  although I must admit I'm  
having trouble figuring out ... why are we attempting such a maneuver?  
The notion of "residuals" around constructed cases makes me  
statistically suspicious, although I suppose that is just some sort of  
cumulative excess/deficit death fraction.

>> http://tolstoy.newcastle.edu.au/R/e4/help/08/06/13508.html
>>
>> predict(mycox1, newdata, type="expected") is not implemented yet.   
>> Dieter
>> suggested to use 'cph' and 'predict.Design', but from my reading so  
>> far, I'm not
>> sure they can do that.
>>
>> Do you other ways to calculate martingale residuals on a new data?
>>
>> Thank you very much!
>>
>> ...Tao

-- 
David Winsemius, MD
West Hartford, CT