How to ensure no statistical differences between groups in covariates when simulating data?

[whymath]

I am simulating data for a 2-groups trial with 100 subjects in each group. There are four variables: GROUP, SUBJNO, SEX, AGE. SEX and AGE are covariates for following model.

Here is my code:

%let seed=12345;

data tab1;
  call streaminit(&seed.);
  length subjno $4 sex $1;
  do _n_=1 to 100;
    group=1;
    subjno='1'||put(_n_,z3.);
    sex=choosec(rand('table',0.5,0.5),'M','F');
    age=rand('integer',18,70);
    output;
  end;

  do _n_=1 to 100;
    group=2;
    subjno='2'||put(_n_,z3.);
    sex=choosec(rand('table',0.5,0.5),'M','F');
    age=rand('integer',18,70);
    output;
  end;
run;

Unfortunately, The initial random seed, 12345, causes SEX statistical difference on different group, the p value of Chisq is 0.0477.

I have tried new seed value like 123, 1234, 123456, 1234567 and they will not cause SEX statistical difference on different group. 

I know there is a possibility that statistical difference of covariates happens. Is there a way to ensure no statistical differences between groups in covariates when simulating data?

Maybe block randomization with covariates as block factor? What about continous covariate variable like AGE?

[Ksharp]

You want this ?

proc plan seed=123;
factors group=2 ordered subj=100 /noprint;
output out=tab1;
quit;
data tab2;
set tab1;
if subj in (1:50) then sex='F';
 else sex='M';
run;
proc freq data=tab2;
table group*sex/ chisq;
run;

[whymath]

Thank you for your reply, would 50:50 be kind of sedulously? And what about continous covariate variable like AGE?

[Ksharp]

Not really,you could use 49: 51 or 48:52 .
About AGE you could try NORMAL distribution other than uniform distribution.