HL test has low power I think, maybe that is reason why SAS don't offer you change number of groups.
I have done it before for SAS-L. Here are SAS Data step code and IML code . Pick up one you like .
data have;
set sashelp.cars(keep=origin type invoice);
call streaminit(1234);
y=rand('bern',.75);
run;
ods select none;
proc logistic data=have ;
class origin type;
model y(event='1')=origin type invoice;
score data=have out=pred_have(keep= y p_1);
run;
ods select all;
proc sort data=pred_have;by p_1;run;
%let groups=20;
proc rank data=pred_have out=group_have groups=&groups ;
var p_1;
ranks rank_p_1;
run;
proc summary data=group_have ;
by rank_p_1;
var y p_1 ;
output out=summary(drop=_type_) sum=observed1 expected1 ;
run;
data summary;
retain rank_p_1 _freq_ observed1 expected1 observed0 expected0;
set summary;
observed0=_freq_-observed1 ;
expected0=_freq_-expected1;
label rank_p_1='Group' _freq_='Total'
observed1 ='Observed(P=1)' expected1='Expected(P=1)'
expected0='Expected(P=0)' observed0='Observed(P=0)';
run;
proc print label noobs ;run;
proc sql noprint;
select sum((observed1-expected1 )**2/expected1 +(observed0-expected0)**2/expected0)
into : chi
from summary;
quit;
data result;
chi=χ
df=&groups-2;
p=1-cdf('CHISQ',chi,df);
label chi='Chi-Square' df='DF' p='Pr > ChiSq';
run;
proc print label noobs ;run;
data have;
set sashelp.cars(keep=origin type invoice);
call streaminit(1234);
y=rand('bern',.75);
run;
ods select none;
proc logistic data=have ;
class origin type;
model y(event='1')=origin type invoice;
score data=have out=pred_have;
run;
ods select all;
proc iml;
use pred_have;
read all var {y p_0 p_1} into x;
close;
groups=20;
call sort(x,3);
nrow=nrow(x);
id=1:nrow;
cutpoints=do(0,nrow+1,(nrow+1)/groups);
g=t(bin(id,cutpoints));
level=unique(g);
n=ncol(level);
all=j(n,6,0); /*Group N O1 E1 O0 E0*/
do i=1 to n;
idx=loc(g=level[i]);
all[i,1]=level[i];
all[i,2]=nrow(g[idx]);
all[i,3]= sum(x[idx,1]=1);
all[i,4]= sum(x[idx,3]);
all[i,5]= sum(x[idx,1]=0);
all[i,6]= sum(x[idx,2]);
end;
print all[l='' c={Group Total Observed1 Expected1 Observed0 Expected0}];
chi=sum((all[,3]-all[,4])##2/all[,4]) + sum((all[,5]-all[,6])##2/all[,6]);
df=groups-2;
p=1-cdf('CHISQ',chi,df);
print chi[l='Chi-Square'] df[l='DF'] p[l='Pr > ChiSq'];
quit;
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