1
Take home
STA 635 (Fall 2005)
Lei Yu
Problem 1
library(survival)
library(rankreg)
data (stanford2)
subset=subset (stanford2, t5 != 'NA' )
rankaft(x=cbind(subset$age,subset$t5), y=log10(subset$time), delta=subset$status)$beta
xnewX1 xnewX2
betag -0.02111191 -0.02654734
betal -0.02452541 -0.11022390
################################
..Repeat the following process..
################################
rankaft(x=cbind(subset$t5), y=(log10(subset$time)-(-0.04021*subset$age)),
delta=subset$status)$beta
xnew
betag 0.000255859
betal -0.098702690
RankRegV(x=cbind(subset$age,subset$t5), y=log10(subset$time), d=subset$status,beta=c(0.04021, 0.000255859))
$VEF
[,1] [,2]
[1,] 991237.41 10798.117
[2,] 10798.12 2568.356
$chisquare
[,1]
[1,] 2.706417
$Pval
[,1]
[1,] 0.2584099
2
#####################################
..Repeat the following process..
#####################################
rankaft(x=cbind(subset$t5), y=(log10(subset$time)-(-0.0037*subset$age)),
delta=subset$status)$beta
xnew
betag -0.04822398
betal -0.11693190
RankRegV(x=cbind(subset$age,subset$t5), y=log10(subset$time), d=subset$status,beta=c(0.0037, -0.04822398))
$VEF
[,1] [,2]
[1,] 996395.36 11871.333
[2,] 11871.33 2884.088
$chisquare
[,1]
[1,] 2.702716
$Pval
[,1]
[1,] 0.2588885
Therefore my 90% confidence interval for the estimate of age alone using the ATF model is
(-0.04021, -0.0037).
Problem 2
I am using PROC PHREG for this problem after importing the cancer dataset into SAS. Since
most of the subjects (95 percent) are 50 years of age and older, I assume the subjects under this
study are basically elder people and share a common baseline hazard in terms of age. I further
assume that the baseline hazard is different between male and female. The option of Efron is used
to handling the ties in the survival time.
/*** Data Step Omitted ***/
proc phreg data=tmp2;
model time*status(1)= age ph_ecog ph_karno /ties=efron;
strata sex;
run;
3
The result is presented as follows, the parameter estimates for age and ph_karno are not
significant indicating age and Karnofsky performance score don’t have significant effect on the
survival time of the cancer patients. While the estimate for ECOG performance score produces a
highly significant p-value. A higher ECOG performance score are therefore more likely
associated with the higher hazard.
The PHREG Procedure
Model Information
Data Set
Dependent Variable
Censoring Variable
Censoring Value(s)
Ties Handling
WORK.TMP2
time
status
1
EFRON
Summary of the Number of Event and Censored Values
Stratum
sex
Total
Event
Censored
Percent
Censored
1
1
136
110
26
19.12
2
2
90
53
37
41.11
------------------------------------------------------------------Total
226
163
63
27.88
Analysis of Maximum Likelihood Estimates
Variable
DF
Parameter
Estimate
Standard
Error
Chi-Square
Pr > ChiSq
Hazard
Ratio
age
ph_ecog
ph_karno
1
1
1
0.01217
0.60752
0.01084
0.00937
0.17782
0.00960
1.6861
11.6723
1.2752
0.1941
0.0006
0.2588
1.012
1.836
1.011
data covals;
input age ph_ecog ph_karno;
cards;
50 1 70
;
run;
proc phreg data=tmp2;
model time*status(1)= age ph_ecog ph_karno /ties=efron;
strata sex;
baseline out=b covariates= covals survival=s logsurv=ls
lower=lcl upper=ucl /nomean;
run;
data c; set b; if sex=1; hazard=-ls; run;
goptions reset=global gunit=pct border cback=white
ctext=black ftitle=zapfb ftext=zapfb htitle=3 htext=2
transparency noborder;
symbol v=circle i=j c=blue w=3;
4
proc gplot;
plot hazard*time; run;
quit;