SAS PHREG
A short introduction
Bahjat Qaqish
General syntax:
PROC PHREG data = dataset1 options1;
MODEL x * event (censored values) = z1 z2 z3
/ options2;
programming statements;
STRATA a (strata definitions similar to proc lifetest) / options3;
TEST equation / options4;
FREQ f;
OUTPUT
OUT=dataset2 keyword1=name / options5;
BASELINE OUT=dataset3 COVARAITES=dataset4 keyword2=name / options6;
BY variables;
Example 1:
A Cox model is fitted to data set A. The model includes the
covariates z1, z2, and z3 and is stratified by sex. Printed output
is suppressed. System file B is created, contains the parameter estimates
and their estimated covariance matrix. Efron's approximation for ties is
used.
proc phreg data=A outest=B noprint covout;
model time * delta(0) = z1 z2 z3 / ties = Efron;
strata sex;
proc print data = B;
Example 2:
The same model is fitted without stratification. No approximation
is used (exact). The parameter estimates and their estimated covariance
and correlation matrices will be printed. 99% confidence intervals for
the relative risk will be printed.
proc phreg data=A;
model time * delta(0) = z1 z2 z3
/ ties=exact covb corrb alpha=0.01 ;
Example 3:
The same model is fitted stratified by grade, separately
within each clinic. Breslow's approximation (the default) is used.
A new system file is generated, system file B. It conatins the same
number of records (observations) as dataset A. It contains the
following variables:
time
= the time variable
delta
= the event variable
z1, z2, z3
= the variables in the regression model
grade
= "strata" variables
clinic = "by" variables
sex, age
= "id" variables
zb
= Z'B
stbzb
= estimated standard error of zb
rj
= size of the risk set when this subject failed or was
censored
s
= estimated survival at the end of followup time for
this subject.
logs
= log s
logch
= log (- log s) = log cumulative hazard estimate
at the end of followup time for this subject.
mi
= martingale residual = delta + logs
devi
= deviance residual
Data set B will be in the same order as data set A (order=data).
The default is sorting by descending time order. The martingale residuals
are plotted against age and z1.
proc phreg data=A;
model time * delta(0) = z1 z2 z3;
id
sex age;
strata grade;
by
clinic;
output out=B
xbeta
= zb
stdxbeta = stdzb
num_left = rj
survival = s
logsurv = logs
loglogs = logch
resmart = mi
resdev
= devi
/ order = data;
proc plot data=B;
plot mi * (age z1);
Example 4:
A model with age and dose is fitted. The estimated survival
curve for a 50 year old given a dose of 10 units is obtaind and plotted.
Another curve is obtained for a 20 year old given the same dose.
By default, the data set generated contains survival estimates evaluated
for values of the covariates equal to the sample mean. The "nomean"
option prevents that.
data Z;
input age dose;
cards;
50
10
20
10
;
proc phreg data=A noprint;
model
time * delta(0) = age dose;
baseline out=B covariates=Z
xbeta
= zb
stdxbeta = stdzb
survival = s
logsurv = logs
loglogs = logch / nomean;
proc plot data=B;
plot s * time = dose;
Example 5:
Time-dependent covariates: see STAN06.SAS.