Hello, I keep getting these two error messages when I run my simulation. I cannot figure out where the error is. I am just posting some part of my code where I feel there may be an error. I know the data looks long but it is pretty much just same line with different numbers. So please go through. If required I will post the complete code. Thank you.
ERROR: (execution) Matrix has not been set to a value.
ERROR: No numeric variables in the dataset
data monika.combined;
set monika.combined;
%let newvars= &group1 &group2 &group3 &group4 &group5 &group6;
array newcoefsa (&k) &group1 &group2 &group3 &group4 &group5 &group6;
array x0a(&k) &wgroup1 &wgroup2 &wgroup3 &wgroup4 &wgroup5 &wgroup6;
array x1a(&k) &mgroup1 &wgroup2 &wgroup3 &wgroup4 &wgroup5 &wgroup6;
array x2a(&k) &mgroup1 &mgroup2 &wgroup3 &wgroup4 &wgroup5 &wgroup6;
array x3a(&k) &mgroup1 &mgroup2 &mgroup3 &wgroup4 &wgroup5 &wgroup6;
array x4a(&k) &mgroup1 &mgroup2 &mgroup3 &mgroup4 &wgroup5 &wgroup6;
array x5a(&k) &mgroup1 &mgroup2 &mgroup3 &mgroup4 &mgroup5 &wgroup6;
array x6a(&k) &mgroup1 &mgroup2 &mgroup3 &mgroup4 &mgroup5 &mgroup6;
xb0=intercept;
xb1=intercept;
xb2=intercept;
xb3=intercept;
xb4=intercept;
xb5=intercept;
xb6=intercept;
* perform white to minority variable distribution switches;
do i=1 to &k;
xb0=xb0+x0a(i)*newcoefsa(i);
xb1=xb1+x1a(i)*newcoefsa(i);
xb2=xb2+x2a(i)*newcoefsa(i);
xb3=xb3+x3a(i)*newcoefsa(i);
xb4=xb4+x4a(i)*newcoefsa(i);
xb5=xb5+x5a(i)*newcoefsa(i);
xb6=xb6+x6a(i)*newcoefsa(i);
end;
pred0=exp(xb0)/(1+exp(xb0));
pred1=exp(xb1)/(1+exp(xb1));
pred2=exp(xb2)/(1+exp(xb2));
pred3=exp(xb3)/(1+exp(xb3));
pred4=exp(xb4)/(1+exp(xb4));
pred5=exp(xb5)/(1+exp(xb5));
pred6=exp(xb6)/(1+exp(xb6));
fhat0=pred0*(1-pred0);
fhat1=pred1*(1-pred1);
fhat2=pred2*(1-pred2);
fhat3=pred3*(1-pred3);
fhat4=pred4*(1-pred4);
fhat5=pred5*(1-pred5);
fhat6=pred6*(1-pred6);
dc1db0=fhat0*one-fhat1*one;
dc2db0=fhat1*one-fhat2*one;
dc3db0=fhat2*one-fhat3*one;
dc4db0=fhat3*one-fhat4*one;
dc5db0=fhat4*one-fhat5*one;
dc6db0=fhat5*one-fhat6*one;
array dc1dba(&k) dc1db1-dc1db&k;
array dc2dba(&k) dc2db1-dc2db&k;
array dc3dba(&k) dc3db1-dc3db&k;
array dc4dba(&k) dc4db1-dc4db&k;
array dc5dba(&k) dc5db1-dc5db&k;
array dc6dba(&k) dc6db1-dc6db&k;
* create other variable components to derivatives;
do i=1 to &k;
dc1dba(i)=fhat0*x0a(i)-fhat1*x1a(i);
dc2dba(i)=fhat1*x1a(i)-fhat2*x2a(i);
dc3dba(i)=fhat2*x2a(i)-fhat3*x3a(i);
dc4dba(i)=fhat3*x3a(i)-fhat4*x4a(i);
dc5dba(i)=fhat4*x4a(i)-fhat5*x5a(i);
dc6dba(i)=fhat5*x5a(i)-fhat6*x6a(i);
end;
proc logistic data=monika.regdata outest=monika.orgcoefs2 covout descending noprint;
model y=&gendervars &newvars / link=logit;
weight wt / normalize;
data monika.covar (drop=&gendervars _link_ _type_ _status_ _name_ _lnlike_);
set monika.orgcoefs2;
* delete coefs and rows associated with racevars;
if _n_=1 or (3<=_n_<=(&r+2)) then delete;
proc means data=monika.combined noprint;
var yw ym pred0-pred6
dc1db0 dc1db1-dc1db&k
dc2db0 dc2db1-dc2db&k
dc3db0 dc3db1-dc3db&k
dc4db0 dc4db1-dc4db&k
dc5db0 dc5db1-dc5db&k
dc6db0 dc6db1-dc6db&k
ordgroup1-ordgroup6;
output out=means1 mean=;
data monika.cont1 (keep=dc1db0 dc1db1-dc1db&k)
monika.cont2 (keep=dc2db0 dc2db1-dc2db&k)
monika.cont3 (keep=dc3db0 dc3db1-dc3db&k)
monika.cont4 (keep=dc4db0 dc4db1-dc4db&k)
monika.cont5 (keep=dc5db0 dc5db1-dc5db&k)
monika.cont6 (keep=dc6db0 dc6db1-dc6db&k);
set monika.means1;
proc iml;
use monika.covar;
read all var _num_ into V;
use monika.cont1;
read all var _num_ into DC1DB;
use monika.cont2;
read all var _num_ into DC2DB;
use monika.cont3;
read all var _num_ into DC3DB;
use monika.cont4;
read all var _num_ into DC4DB;
use monika.cont5;
read all var _num_ into DC5DB;
use monika.cont6;
read all var _num_ into DC6DB;
VAR1=DC1DB*V*t(DC1DB);
VAR2=DC2DB*V*t(DC2DB);
VAR3=DC3DB*V*t(DC3DB);
VAR4=DC4DB*V*t(DC4DB);
VAR5=DC5DB*V*t(DC5DB);
VAR6=DC6DB*V*t(DC6DB);
create monika.vardata var {var1 var2 var3 var4 var5 var6};
append;
data monika.means1 (keep=yw ym pred0-pred6 var1-var6 cont1-cont6 ordgroup1-ordgroup6);
merge monika.means1 monika.vardata;
cont1=pred0-pred1;
cont2=pred1-pred2;
cont3=pred2-pred3;
cont4=pred3-pred4;
cont5=pred4-pred5;
cont6=pred5-pred6;
data monika.means1 (keep = yw ym contg1-contg6 vargroup1-vargroup6);
set monika.means1;
array ordgroupa{6} ordgroup1-ordgroup6;
array contgroupa{6} contg1-contg6;
array vargroupa{6} vargroup1-vargroup6;
array conta{6} cont1-cont6;
array vara{6} var1-var6;
do j = 1 to 6;
do i = 1 to 6;
if ordgroupa[j] = i then do;
contgroupa[j] = conta[i];
vargroupa[j] = vara[i];
end;
end;
end;
data monika.means2;
set monika.means2 monika.means1;
run;
%end;
%mend;
run;
options nonotes;
%simulate;
run;
proc means data=monika.means2;
title2 'Mean Values of Contribution Estimates from Simulations';
var yw ym contg1-contg6 vargroup1-vargroup6;
output out=monika.meandecomp mean=;
data monika.meandecomp;
merge monika.meandecomp monika.ywdata monika.ymdata;
gap=ymfull-ywfull;
perc1=contg1/gap;
perc2=contg2/gap;
perc3=contg3/gap;
perc4=contg4/gap;
perc5=contg5/gap;
perc6=contg6/gap;
se1=sqrt(vargroup1);
se2=sqrt(vargroup2);
se3=sqrt(vargroup3);
se4=sqrt(vargroup4);
se5=sqrt(vargroup5);
se6=sqrt(vargroup6);
label contg1=&labelgroup1;
label contg2=&labelgroup2;
label contg3=&labelgroup3;
label contg4=&labelgroup4;
label contg5=&labelgroup5;
label contg6=&labelgroup6;
options label;
proc means data=monika.meandecomp mean;
title2 'Final Output for Table - Means Values for Contribution Estimates';
var ywfull ymfull gap
contg1 se1 perc1 contg2 se2 perc2 contg3 se3 perc3 contg4 se4 perc4
contg5 se5 perc5 contg6 se6 perc6;
run;
