SAS Survival Analysis III: Cox model

libname asa_data 'C:\ASA_SAS';
ods trace on;
proc phreg data = asa_data.whas100;
model lenfol*fstat(0) = gender;
run;
ods trace off;
* Table 3.2;
ods output ParameterEstimates = temp1;
proc phreg data = asa_data.whas100;
model lenfol*fstat(0) = gender;
run;
libname asa_data 'C:\ASA_SAS';
ods trace on;
proc phreg data = asa_data.whas100;
model lenfol*fstat(0) = gender;
run;
ods trace off;
* Table 4.2;
ods output ParameterEstimates = temp1;
proc phreg data = asa_data.whas100;
model lenfol*fstat(0) = gender / ties = breslow;
run;
proc print data = temp1;run;
proc contents data = temp1;run;
data table4p2;
set temp1;
z = sqrt(ChiSq);
z2 = Estimate / StdErr;
lowerb = estimate - 1.96*stderr;
upperb = estimate + 1.96*stderr;
run;

proc print data = table4p2 label noobs;
var Parameter Estimate stderr z z2 Probchisq lowerb upperb;
format Estimate z z2 Probchisq lowerb upperb f8.3;
format stderr f8.4;
label Parameter = 'Variable'
   Estimate = 'Coeff.'
      stderr = 'Std.Err.'
   Probchisq = 'p>|z|'
   lowerb = 'Conf Lower'
   upperb = 'Conf Upper';
run;

* Table 4.4;
data temp2;
set asa_data.whas100;
age_2 = 0;
age_3 = 0;
age_4 = 0;
if 60 <= age <= 69 then age_2 = 1;
else if 70 <= age <= 79 then age_3 = 1;
else if 80 <= age then age_4 = 1;  
run;
* Table 4.5 & Table 4.7;
proc phreg data = temp2;
model lenfol*fstat(0) = age_2 age_3 age_4 / ties = breslow risklimits covb;
run;

data temp3;
set asa_data.whas100;
age_2 = 0;
age_3 = 0;
age_4 = 0;
if age < 60 then do;
age_2 = -1;
age_3 = -1;
age_4 = -1;
end;
if 60 <= age <= 69 then age_2 = 1;
if 60 <= age <= 69 then age_2 = 1;
else if 70 <= age <= 79 then age_3 = 1;
else if 80 <= age then age_4 = 1;  
run;
* Table 4.8;
proc phreg data = temp3;
model lenfol*fstat(0) = age_2 age_3 age_4 / ties = breslow risklimits covb;
run;

* Table 4.13;
* Crude Model;
proc phreg data = asa_data.whas500;
model lenfol*fstat(0) = gender/ risklimits;
run;
* Adjusted Model;
proc phreg data = asa_data.whas500;
model lenfol*fstat(0) = gender age/ risklimits;
run;
* Interaction Model;
proc phreg data = asa_data.whas500;
model lenfol*fstat(0) = gender age gender*age/ risklimits; *no hazard ratio in this case;
run;
proc phreg data = asa_data.whas500;
model lenfol*fstat(0) = gender age ga/ risklimits;
ga = gender*age;
output out = temp4 xbeta = xbeta;
run;
proc print data = temp4; run;
proc gplot data = temp4;
plot xbeta*age = gender;
run;
* Figure 4.5;
data temp1;
set asa_data.gbcs;
time = rectime/30;
run;
proc phreg data = temp1;
model time*censrec(0) = hormone;
output out = temp2 survival = survival;
run;
proc sort data = temp2;
by hormone time;
run;
proc gplot data = temp2;
plot survival*time = hormone;
run;
quit;

libname asa_data 'C:\ASA_SAS';
* Figure 5.2a;
proc phreg data = asa_data.whas500;
model lenfol*fstat(0) = age hr diasbp gender chf;
id id;
output out = fig52a resmart = mart;
run;
proc sort data = asa_data.whas500;
by id;
run;
proc sort data = fig52a;
by id;
run;
data fig52a;
merge fig52a asa_data.whas500;
by id;
run;
proc loess data = fig52a;
model mart = bmi;
ods output outputstatistics = temp1;
run;
proc sort data = temp1;
by bmi;
run;
proc contents data = temp1; run;
goptions reset = all;
symbol1 v = dot i = none;
symbol2 v = none i = join;
proc gplot data = temp1;
plot DepVar*bmi=1 pred*bmi=2 / overlay;
*plot pred*bmi=2;
run;
quit;

* Stepwise ;
proc phreg data = asa_data.whas500;
model lenfol*fstat(0) = age chf hr diasbp bmi gender mitype miord sysbp cvd afb
/ selection = forward slentry = 0.25 slstay = 0.8;
run;
proc phreg data = asa_data.whas500;
model lenfol*fstat(0) = age chf hr diasbp bmi gender mitype miord sysbp cvd afb
/ selection = stepwise slentry = 0.25 slstay = 0.8 details;
run;
* Best Subset;
proc phreg data = asa_data.whas500;
model lenfol*fstat(0) = age chf hr diasbp bmi gender mitype miord sysbp cvd afb
/ selection = score best = 3 details;
run;