[R] Contrasts in coxph

[David Winsemius]

On 4/5/21 8:28 PM, Sorkin, John wrote:
> I would like to define contrasts on the output of a coxph function. It appears that the contrast function from the contrast library does not have a method defined that will allow computation of contrasts on a coxph object.
>
> How does one define and evaluate contrasts for a cox model?


I suspect that you are hoping for post-hoc pairwise contrasts. If that's 
the case, then the multcomp package's glht is generally very capable. It 
has three examples in its vignette the involve survivla models. The last 
one constructs a categorical variable for age. That's not a procedure 
that I endorse, but it may have been done for illustration of a method 
and would therefore be free of sin.


library(multcomp)  # console output follows

 > if (require("survival") && require("MASS")) {
+     ### construct 4 classes of age
+     Melanoma$Cage <- factor(sapply(Melanoma$age, function(x){if( x <= 
25 ) return(1)
+         if( x > 25 & x <= 50 ) return(2)
+         if( x > 50 & x <= 75 ) return(3)
+         if( x > 75 & x <= 100) return(4) }
+     ))
+ }
 > summary(Melanoma)
       time          status          sex age             year        
thickness
  Min.   :  10   Min.   :1.00   Min.   :0.0000   Min.   : 4.00 Min.   
:1962   Min.   : 0.10
  1st Qu.:1525   1st Qu.:1.00   1st Qu.:0.0000   1st Qu.:42.00 1st 
Qu.:1968   1st Qu.: 0.97
  Median :2005   Median :2.00   Median :0.0000   Median :54.00 Median 
:1970   Median : 1.94
  Mean   :2153   Mean   :1.79   Mean   :0.3854   Mean   :52.46 Mean   
:1970   Mean   : 2.92
  3rd Qu.:3042   3rd Qu.:2.00   3rd Qu.:1.0000   3rd Qu.:65.00 3rd 
Qu.:1972   3rd Qu.: 3.56
  Max.   :5565   Max.   :3.00   Max.   :1.0000   Max.   :95.00 Max.   
:1977   Max.   :17.42
      ulcer       Cage
  Min.   :0.000   1: 14
  1st Qu.:0.000   2: 73
  Median :0.000   3:104
  Mean   :0.439   4: 14
  3rd Qu.:1.000
  Max.   :1.000
 > cm <- coxph(Surv(time, status == 1) ~ Cage, data = Melanoma)
 > ### specify all pair-wise comparisons among levels of "Cage"
 > cm.glht <- glht(cm, mcp(Cage = "Tukey"))
 > cm.glht

      General Linear Hypotheses

Multiple Comparisons of Means: Tukey Contrasts


Linear Hypotheses:
            Estimate
2 - 1 == 0  -0.2889
3 - 1 == 0   0.1910
4 - 1 == 0   1.0742
3 - 2 == 0   0.4800
4 - 2 == 0   1.3631
4 - 3 == 0   0.8832


-- 

David.

>
> Thank you,
> John
>
> John David Sorkin M.D., Ph.D.
> Professor of Medicine
> Chief, Biostatistics and Informatics
> University of Maryland School of Medicine Division of Gerontology and Geriatric Medicine
> Baltimore VA Medical Center
> 10 North Greene Street
> GRECC (BT/18/GR)
> Baltimore, MD 21201-1524
> (Phone) 410-605-7119
> (Fax) 410-605-7913 (Please call phone number above prior to faxing)
>
>
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