How to conditionally process variables?

[TX_STAR]

Dear members,

I am doing a simulation in SAS. I generated (1000 cases and 53 variables). 53 variables include Id and 52 vars: i1 to 140 is either 0 or 1, i41 to i52 is either 1, 2 or 3.  The data looks like below.

ID     i1 to i52

0001 0010001000110100111111111001100101010000113211313133
0002 0111000011011001010011001011001100000100131111211112
0003 0010010001101100110111100011110110000101111111123122
0004 1111111111111111111011111111111111111101333322333332
0005 1111111111111111110111110011111101111101333312333332
0006 0111000000011001101101101011000110100100133121311121

.

.

I want to randomly select 4 vars from 52 vars and replace the values with blank. This needs to done for the first 20 cases (out of 1000). The randomly selected 4 vars are different for each case.  (need loop here)

How to randomly select 4 variables? And how should I conditionally process variables to replace the values with missing?

Thanks so much!

[PGStats]

Put your variables in an array, then

Select a random index

if the array element is not missing, set it to missing
repeat until you have set 4 values to missing.

[TX_STAR]

Hi PG,

Thanks.

I was able to generate random index and put it in macro variable and use it in arrays as below.

Now I want to do loop for the first 20 cases (such as do _n_=1 to 20) so that each case have a different set of 48 randomly selected variable with missing and 4 without (in the original question, the number of variables with missing is 4, without is 48. Sorry for the confusion). 

How can I put the following code together to loop for the first 20 cases (out of 1000)?

--------------------------------------- sas code---------------------------------------------------------------------------------------------------------------
data _null_;
call streaminit(1234);
run;

proc sql /*noprint */;
create table all_vars as
select name
from sashelp.vcolumn /*DICTIONARY.COLUMNS*/
where libname = 'WORK' AND memname = 'MATH' AND NAME not in ( 'ID' 'bucket')
order by rand('uniform')
;
quit;

ata nomiss miss;
set all_vars;
if _n_ le 4
then output nomiss;
Else output miss;
run;

proc sql noprint;
select name into :mvarlist separated by ' ' from miss;
select name into :nmvarlist separated by ' ' from nomiss;
quit;
%put "list of variables with missing:&mvarlist.";
%put "list of variables without missing:&nmvarlist.";

data math_w_miss;
set math;
if bucket = 0 then do;
array miss [48] &mvarlist.;
array nmiss [4] &nmvarlist.;
do m=1 to 48;
miss{m}=.;
end;
do n=1 to 4;
nmiss{n}=nmiss{n};
end;
end;
run;

[PeterClemmensen]

A bit smoother than my first approach

data have(drop=j);
   format ID;
   array i{52};
   do ID=1 to 1000;
      do j=1 to dim(i);
         i[j]=floor(4*rand('uniform'));
      end;
      output;
   end;
   format ID z4.;
run;

data want;
   set have;
   array iVars i1-i52;
   array idx idx1-idx4;
   if _N_=1 then do over idx;
      idx=ceil(52*rand('uniform'));
   end;
   if _N_<=20 then do;
      call missing(iVars[idx1], iVars[idx2],iVars[idx3],iVars[idx4]);
   end;
   retain idx:;
   drop idx:;
run;

[PeterClemmensen]

There is definitely a smoother way, but using brute force, you can do something like this

data have(drop=j);
   format ID;
   array i{52};
   do ID=1 to 1000;
      do j=1 to dim(i);
         i[j]=floor(4*rand('uniform'));
      end;
      output;
   end;
   format ID z4.;
run;

data want;
   set have;
   array iVars i1-i52;
   if _N_=1 then do;
      idx1=ceil(52*rand('uniform'));
      idx2=ceil(52*rand('uniform'));
      idx3=ceil(52*rand('uniform'));
      idx4=ceil(52*rand('uniform'));
   end;
   if _N_<=20 then do;
      call missing(iVars[idx1], iVars[idx2],iVars[idx3],iVars[idx4]);
   end;
   retain idx:;
   drop idx:;
run;

[TX_STAR]

Hi Draycut,

I modified your code and got what close to what I need. but I have two issues:

(1) I want 48 of 52 items have missing. however, my array..idx[j] did not work. I did it manually. The code looks like below. Is there a way to do array for idx so that the coding is easier?

(2) the idx1 to idx48 using the code below (idx1=ceil(52*rand('uniform'));) are not unique. How to add seed there so that the 48 idx are unique?

The generated data looks like below. there should be 48 blanks for each person. but due to duplicated idx, the number of blanks is <48.

Thanks,

 /*-------------------------------------- sas code----------------------------------------------------------------*/

data want;
set have;
array iVars i1-i52;

if _N_<=20 then do;

idx1=ceil(52*rand('uniform'));
idx2=ceil(52*rand('uniform'));
idx3=ceil(52*rand('uniform'));
idx4=ceil(52*rand('uniform'));
.

.

.
idx45=ceil(52*rand('uniform'));
idx46=ceil(52*rand('uniform'));
idx47=ceil(52*rand('uniform'));
idx48=ceil(52*rand('uniform'));

call missing(iVars[idx1],iVars[idx2],iVars[idx3],iVars[idx4],........,iVars[idx45],iVars[idx46],iVars[idx47],iVars[idx48]);
end;
retain idx:;
drop idx:;
run;

SAS Output

Obs	ID	i1	i2	i3	i4	i5	i6	i7	i8	i9	i10	i11	i12	i13	i14	i15	i16	i17	i18	i19	i20	i21	i22	i23	i24	i25	i26	i27	i28	i29	i30	i31	i32	i33	i34	i35	i36	i37	i38	i39	i40	i41	i42	i43	i44	i45	i46	i47	i48	i49	i50	i51	i52
1	0001	0		2				0				0		2				0		2	1			2		1				2		1			3	3	3		2		3						2		3			2
2	0002	1	3			2		1						0		2				2	0	2					0	0	2			2		0	2						2		2				2	0	0	3	3
3	0003	2	3		0	0										0	3			2	3						1		1	0	2	1						1			0		1			2	2	1		0	2
4	0004	0	0	3	3	2	2				1				2		0	0	2			2		2				2				0	2							2			3		0						2
5	0005		0			1		2					1			2			0		1		0	2			0	1	2		2			3				2	2				0			0		0	1		3
6	0006		1				1		0	2		0		3					3	1		1							3	3		1	2	0	2	3	0	1	3	1	0				2					0	2
7	0007	3				0					3		1		0					0					0	2	3			3	2	2			1		1		3		0	0				3	3					3	0
8	0008			0			0		3			1	1			3		1	3	0	1	0	2		2		1		1		0			0	1	0							2		1				3		2	1
9	0009			0	3		1				0		2		3		2		0			3		3					1			3			2	2						2	3		3		3	2	1				1
10	0010	1	0	2				0	3		0												0			1	1									0				1		3		2	1	2		1		0			0
11	0011		1				1	2		2		1				0	0						0		2		2	2	1					2			0	2			1			2	1	0		2	1
12	0012			2		2			3	1		3			3					2			2				3	0			0		1	3		0	3						0		3			0				2
13	0013		3						0	1	0		0	3							2		1		0				3					3		3	0			0		0	1	0				1				0	3
14	0014		3	3		0	3		1			2	1		0		3		1	2	2	2		3				3						1	0	1			0						3						3	0
15	0015		3		3			0	0	0		2						0	3		0		3						3				3	0	0		2	0		1					3		2		0		3
16	0016						0				3		2	0		2		1	3	3	1		1		0			1	0		2									3			3					1		3		3	3
17	0017					3			0				2			2			2						2	1				3	1	2	2		0		3		2				3		3		0	2		3	1
18	0018						2									0			2	1	3		2	2			0		2				3	0		0	0	3					3			0	2	0	1	3	2		3
19	0019	1	3			1			1				2		3		3	0						3	0	0	3			2						3	2	2		1				2	2					3	2	2
20	0020	0	1		2		0						2	2				0					3			2						3					1	2			1							1			3		3
21	0021	2	0	0	1	1	2	3	0	0	2	2	1	2	2	0	2	2	3	0	3	3	2	0	1	3	3	2	2	1	3	3	3	1	0	3	3	3	0	1	3	2	0	0	3	1	2	0	2	1	1	2	3
22	0022	1	0	2	3	3	2	1	2	1	1	2	3	0	1	3	2	0	2	0	3	1	1	0	1	3	1	1	2	1	1	3	1	1	0	3	1	0	1	1	3	3	3	1	2	0	0	3	0	1	0	3	2
23	0023	1	0	2	1	3	0	0	3	1	0	2	0	3	1	2	0	1	1	3	0	3	2	0	1	0	0	1	1	1	2	0	2	3	3	3	3	1	3	1	2	2	2	0	2	3	2	0	3	0	0	1	2
24	0024	2	0	0	0	0	0	2	1	1	0	0	1	0	2	0	1	3	0	2	0	3	3	3	3	0	1	0	2	0	2	2	2	3	2	2	1	0	1	0	2	1	1	2	0	1	2	3	2	2	0	0	3
25	0025	3	1	2	3	1	3	2	3	2	3	0	0	2	2	1	0	1	3	2	1	2	1	3	1	0	0	1	3	0	3	1	2	2	0	1	2	0	0	0	3	3	0	0	0	3	3	0	2	3	0	2	1
26	0026	0	0	2	1	3	2	2	2	3	0	2	1	1	2	2	0	0	1	1	3	0	2	2	2	2	1	3	3	1	2	0	3	1	1	3	2	3	2	0	2	3	2	1	1	3	1	1	0	2	2	1	0
27	0027	0	0	1	0	2	0	3	2	3	1	0	0	1	1	0	3	3	0	0	1	1	0	0	3	3	1	1	3	0	2	0	3	3	0	2	3	3	3	2	2	0	1	2	1	0	2	0	1	1	0	3	3
28	0028	1	3	1	3	3	3	2	2	3	2	0	0	1	1	1	3	0	1	3	1	1	2	1	1	1	1	3	1	2	0	1	1	1	2	1	0	3	1	2	1	1	0	3	2	2	1	0	1	3	0	3	2
29	0029	1	3	1	1	2	3	2	0	1	2	2	2	0	1	2	1	1	2	0	0	3	0	1	3	1	1	2	0	0	0	0	1	3	0	1	1	1	0	1	0	1	0	0	0	0	3	3	0	1	3	3	1
30	0030	0	1	2	3	1	3	0	1	2	1	3	0	2	1	3	2	2	1	1	0	1	3	1	1	3	2	2	1	2	2	1	3	1	0	3	3	0	1	2	0	2	0	2	3	3	0	3	1	0	2	3	3
31	0031	2	1	0	1	1	2	0	1	2	2	0	1	3	2	3	3	0	3	2	0	0	2	0	2	2	1	0	3	0	0	1	1	1	2	0	3	0	2	2	3	3	3	0	0	1	3	1	1	2	1	3	0
32	0032	2	0	1	3	1	2	3	2	3	2	2	0	2	0	3	1	1	2	1	2	0	3	1	2	1	3	1	1	2	2	1	3	0	0	0	1	3	0	2	3	2	1	3	2	0	1	3	2	3	1	0	1
33	0033	2	2	0	3	1	1	2	2	1	1	0	0	0	2	2	0	0	2	3	0	3	0	0	1	0	3	3	2	2	2	3	2	2	1	3	0	1	0	1	3	1	0	0	0	3	3	2	3	0	3	2	3
34	0034	3	3	2	1	3	3	0	1	3	1	3	2	0	3	3	2	1	1	0	2	3	0	2	0	2	0	2	3	0	2	0	0	2	2	1	0	3	0	3	1	0	2	1	0	1	1	3	0	1	3	0	1
35	0035	1	0	2	2	3	0	0	1	0	0	0	1	3	2	1	3	3	1	3	3	2	1	2	1	1	3	1	2	2	0	1	3	0	3	0	3	2	0	0	1	0	2	3	1	1	2	1	3	3	1	1	0
36	0036	1	1	2	3	1	2	0	2	2	2	3	1	0	1	2	0	1	1	0	1	1	0	2	1	1	1	0	1	2	1	0	3	3	2	3	0	1	2	2	0	2	2	2	1	0	0	0	3	1	2	2	2
37	0037	2	3	3	2	3	1	1	1	3	1	3	1	0	2	1	0	1	3	3	2	1	1	1	2	0	1	1	1	0	3	3	1	1	0	1	0	1	0	3	0	2	3	2	2	1	0	2	1	2	0	1	3
38	0038	3	3	0	3	2	1	3	2	0	3	2	3	2	2	1	0	0	3	1	3	2	0	0	0	2	1	2	1	0	2	2	2	0	3	3	1	3	3	2	1	0	0	3	2	0	0	3	1	2	1	1	2
39	0039	1	1	0	2	1	0	1	0	2	3	3	1	2	3	3	2	3	0	1	1	1	2	3	2	3	1	3	0	3	1	0	0	1	3	1	1	2	0	1	0	3	0	2	1	1	2	3	1	3	2	1	0
40	0040	0	0	2	0	0	3	3	3	2	3	3	2	0	3	1	2	0	0	3	0	1	0	1	2	3	0	0	0	2	1	1	0	0	1	3	3	1	0	1	0	0	0	3	3	1	1	2	3	2	0	1	3
41	0041	2	1	1	0	2	0	1	0	1	1	2	1	2	2	0	1	1	2	2	1	0	3	1	2	3	0	3	1	2	2	2	1	1	0	2	1	0	3	0	2	0	1	0	1	2	1	2	2	1	0	0	2
42	0042	0	0	3	3	1	1	1	2	0	1	0	1	2	0	2	3	1	2	2	2	1	1	3	0	2	1	0	0	0	2	1	2	3	0	0	1	2	3	1	3	3	1	0	1	3	2	1	1	1	3	0	2
43	0043	1	0	1	1	1	1	3	0	1	1	3	0	0	1	0	3	1	2	1	2	0	3	3	1	0	2	0	3	0	0	2	2	3	1	0	3	1	0	2	1	0	1	2	1	1	2	3	2	0	3	0	1
44	0044	1	2	0	3	2	2	1	0	2	0	0	2	3	3	2	2	2	1	0	0	1	0	2	2	0	2	3	3	1	0	0	2	0	3	1	1	2	1	1	1	1	1	2	2	0	1	0	3	3	2	3	3
45	0045	1	1	2	2	0	3	0	0	2	0	1	1	3	2	0	1	0	3	2	2	0	3	1	1	1	2	3	1	2	3	0	0	0	1	3	3	0	1	2	0	0	1	0	0	1	2	1	1	2	2	2	3
46	0046	3	3	3	2	3	3	2	0	3	1	1	1	0	1	1	1	1	3	3	0	2	0	1	2	3	0	3	2	2	3	2	1	2	3	2	1	1	2	0	0	3	3	3	1	0	2	0	0	2	1	1	1
47	0047	3	3	1	3	0	0	3	2	2	1	1	0	3	2	3	3	3	2	0	2	1	0	3	3	2	3	3	3	0	0	0	3	2	0	1	2	2	1	0	3	0	1	0	2	3	3	2	2	2	3	0	1
48	0048	1	1	2	2	0	3	3	3	1	0	3	0	0	0	1	1	0	3	2	2	0	3	0	1	3	3	0	3	3	1	2	0	3	1	3	3	3	3	1	3	0	2	2	2	0	2	3	2	0	3	0	1
49	0049	2	2	0	1	2	3	0	3	3	3	0	0	1	1	2	0	2	3	0	2	1	2	2	3	1	0	2	3	1	3	2	2	1	0	1	2	2	3	0	3	1	3	0	3	1	3	3	1	0	1	0	2
50	0050	2	0	0	3	3	0	2	2	3	2	0	3	3	3	2	0	3	2	0	2	3	0	1	3	3	0	3	2	1	3	0	2	1	3	3	2	1	1	2	0	3	2	2	0	3	2	0	0	0	2	1	0
51	0051	1	0	3	2	1	3	1	0	0	2	3	2	1	1	0	1	3	0	1	2	0	3	2	1	2	2	2	3	2	0	0	0	1	3	2	1	0	3	1	0	3	3	3	1	1	0	2	1	1	1	0	0
52	0052	0	0	0	1	1	1	1	3	0	0	0	1	3	3	2	1	1	3	0	3	3	2	3	2	1	3	2	0	1	0	0	1	1	2	1	2	3	0	2	3	0	1	1	3	2	0	0	3	3	0	1	2
53	0053	0	0	1	0	0	3	1	3	3	0	2	1	1	0	3	3	1	0	2	0	0	2	3	1	0	1	3	0	0	0	3	1	0	1	1	1	0	1	1	1	0	2	0	2	3	3	3	1	3	3	2	2
54	0054	0	0	3	1	3	1	2	0	3	0	0	0	0	1	0	1	0	1	2	2	2	3	2	3	0	0	1	3	0	1	1	1	1	0	1	1	2	1	1	2	2	3	3	1	3	0	1	1	0	0	3	0
55	0055	1	3	1	1	3	3	0	1	1	2	3	0	1	3	1	2	2	0	3	2	2	1	1	1	2	1	0	2	3	2	2	3	1	1	1	2	0	3	3	3	3	1	2	2	2	0	0	0	0	3	0	0
56	0056	2	0	2	0	1	3	2	3	0	1	1	3	1	2	2	2	3	2	2	1	0	0	3	1	2	3	0	1	3	3	0	0	0	2	1	2	3	3	2	1	1	2	1	1	1	3	3	3	3	2	0	3
57	0057	2	1	2	1	0	2	3	1	3	3	3	2	0	0	1	1	3	1	1	0	1	1	1	1	3	1	1	2	1	2	1	0	3	2	2	3	0	1	1	3	3	0	2	0	3	2	3	2	0	1	3	2
58	0058	1	2	3	2	1	3	2	0	3	1	1	3	1	1	2	1	1	3	2	0	1	1	1	3	3	2	2	1	2	1	1	2	1	1	2	2	1	2	0	2	1	0	3	0	1	2	0	3	1	3	1	0
59	0059	3	3	3	0	3	0	1	1	0	3	3	1	0	3	2	1	0	3	2	0	1	3	1	1	3	3	1	3	1	0	2	1	3	2	1	0	2	3	3	3	1	3	0	1	0	0	2	2	1	2	0	3
60	0060	0	2	2	2	0	3	1	2	1	3	2	1	1	3	3	2	2	3	0	3	1	2	2	3	1	0	2	2	3	2	3	2	1	2	2	0	3	1	0	0	0	0	1	1	3	0	3	3	1	3	0	2
61	0061	1	2	0	1	0	2	3	1	1	0	2	1	0	1	2	2	1	0	1	3	1	0	0	0	1	0	0	1	0	1	2	0	3	0	3	0	3	0	3	1	2	3	2	0	0	2	3	1	3	1	3	0
62	0062	2	0	0	3	1	3	3	0	1	1	3	2	0	3	0	0	0	1	0	2	3	1	0	3	2	0	3	3	2	2	1	0	0	0	3	3	1	2	3	0	1	0	1	2	3	0	1	2	1	0	3	2
63	0063	1	3	3	0	2	2	0	1	2	1	0	2	2	1	0	1	3	3	1	3	2	1	1	1	0	1	1	3	3	3	2	0	1	0	0	0	0	3	0	0	1	2	0	1	0	1	0	3	0	3	3	0
64	0064	1	1	0	0	0	1	3	1	0	1	2	1	0	0	0	0	0	0	3	0	1	2	3	0	1	0	1	1	1	1	2	0	0	0	0	0	1	1	0	3	3	0	1	2	3	0	1	2	2	2	1	2
65	0065	0	2	0	2	0	2	2	2	3	1	2	3	1	1	1	2	1	1	1	0	0	1	1	3	2	2	3	2	0	0	1	0	1	3	2	2	1	2	3	3	1	3	1	0	2	1	2	2	0	1	2	0
66	0066	0	2	0	0	0	1	0	0	1	3	1	0	0	0	1	3	0	3	3	2	1	3	1	3	0	3	3	0	1	1	3	1	0	1	1	3	3	1	1	0	0	0	0	2	2	1	3	3	2	1	1	3
67	0067	3	0	3	0	3	1	0	1	2	1	0	3	1	2	2	3	3	2	3	1	1	1	3	0	2	2	1	1	2	1	2	3	3	3	0	2	1	2	1	1	0	1	0	1	3	1	2	2	3	2	0	2
68	0068	1	0	2	2	3	0	2	2	0	0	0	2	1	1	2	0	2	0	1	3	0	3	0	0	0	1	0	3	2	3	3	1	2	3	0	0	1	2	3	3	1	3	1	2	0	0	0	3	0	2	1	2
69	0069	2	1	3	3	0	0	2	1	2	2	0	2	3	1	0	0	1	3	2	1	2	0	1	3	0	3	1	3	0	3	3	0	0	2	1	0	1	0	0	3	0	1	3	0	0	3	2	3	2	1	0	2
70	0070	1	0	3	0	1	2	3	1	3	0	0	1	1	0	0	0	2	0	1	0	1	2	1	1	1	0	3	1	2	2	1	1	2	0	2	0	2	1	3	2	0	3	3	3	1	1	3	0	3	0	0	0
71	0071	0	2	1	2	2	3	0	3	2	1	2	3	0	3	3	1	0	2	1	3	2	3	1	0	3	0	1	2	2	2	0	0	2	1	1	2	2	0	3	0	3	0	0	1	2	3	0	2	3	2	3	1
72	0072	0	2	1	3	3	3	2	0	2	0	1	2	3	3	0	1	1	2	3	1	3	2	1	2	3	3	2	2	3	2	0	1	1	2	3	3	1	2	0	2	0	0	0	1	1	1	0	3	2	0	3	3
73	0073	2	1	1	2	1	2	1	1	2	1	2	3	0	2	1	2	1	3	3	2	3	1	1	1	1	2	0	3	3	1	0	1	2	0	3	0	3	2	2	1	1	2	1	0	2	0	1	1	2	2	2	1
74	0074	2	1	1	2	0	2	1	0	3	1	1	2	1	3	2	0	2	1	2	3	1	1	1	0	0	2	0	0	2	0	3	2	2	3	0	1	3	1	0	2	2	2	0	0	0	3	2	1	0	0	3	3
75	0075	3	2	0	2	1	0	2	3	2	2	1	3	3	3	2	2	2	1	1	1	3	0	1	0	0	0	1	0	3	2	3	1	1	2	0	1	1	2	1	1	2	2	0	2	3	1	1	0	0	2	2	2
76	0076	0	2	2	2	2	2	0	0	0	2	1	1	2	0	2	1	3	3	3	3	1	1	3	0	0	0	0	0	1	3	1	3	0	0	0	1	0	2	2	0	0	3	3	2	1	2	1	2	2	0	3	2
77	0077	2	3	1	0	1	2	2	2	0	0	1	0	2	2	0	1	1	3	2	1	1	0	1	0	0	2	1	1	3	1	3	3	3	2	0	3	1	1	1	2	0	2	3	3	2	3	0	2	3	0	2	2
78	0078	0	2	0	3	2	1	3	0	2	3	2	3	3	1	0	1	0	0	0	2	3	1	2	2	1	2	1	3	3	3	3	1	0	3	2	0	1	0	0	0	3	1	3	3	3	3	0	3	3	1	3	3
79	0079	3	0	1	1	2	2	3	1	3	3	2	2	2	0	2	0	0	1	2	2	3	2	3	1	0	1	0	1	3	0	3	2	2	2	2	0	2	2	2	1	1	1	1	1	1	3	0	1	3	0	3	0
80	0080	1	3	1	1	2	2	1	0	1	0	3	1	3	2	3	0	2	3	3	3	3	2	2	3	1	1	1	1	0	1	2	0	0	0	3	1	0	0	0	3	0	1	0	2	0	2	3	1	0	0	1	0
81	0081	2	1	0	0	3	1	3	2	3	0	0	2	2	3	3	0	1	2	0	3	0	0	1	3	0	0	0	3	1	3	3	3	0	3	3	1	2	2	3	1	3	0	3	1	2	3	1	1	2	2	0	3
82	0082	1	3	1	0	0	0	3	1	0	2	0	1	0	0	0	0	1	1	3	1	1	0	3	2	0	0	0	1	2	1	2	3	3	3	0	1	1	3	3	3	3	2	3	1	0	2	0	0	2	0	0	3
83	0083	3	2	1	2	0	1	2	0	3	2	1	2	2	1	3	2	1	3	1	2	1	0	0	1	2	1	0	0	2	1	1	3	3	0	3	0	0	0	1	1	2	0	3	0	0	1	2	2	0	0	3	0
84	0084	0	2	1	1	3	2	3	2	1	1	2	2	1	1	2	3	2	2	2	3	1	2	1	3	1	3	0	1	0	0	2	1	0	3	1	0	2	1	1	2	2	0	3	3	2	0	0	2	2	1	3	1
85	0085	3	3	1	1	2	0	0	2	2	0	2	3	3	3	3	2	2	3	0	3	1	3	0	3	1	0	0	3	2	3	2	1	3	1	2	1	0	0	2	0	3	3	3	2	3	3	1	2	2	3	0	3
86	0086	3	2	2	2	3	3	1	2	0	3	0	3	2	3	2	3	3	1	2	2	0	0	1	1	3	0	3	2	2	2	3	1	1	0	2	1	3	2	2	2	1	0	0	1	3	3	1	0	3	0	0	3
87	0087	0	1	3	1	3	3	2	1	0	1	1	3	2	3	0	1	3	0	1	1	3	0	2	1	0	0	1	0	3	2	0	3	2	3	2	1	1	0	3	1	3	3	0	2	1	2	0	1	2	1	0	0
88	0088	1	0	0	1	2	3	1	3	0	0	2	0	3	3	0	3	1	2	0	3	0	1	3	1	0	0	0	0	0	2	0	2	1	2	0	2	3	0	0	0	3	2	1	2	3	1	2	1	0	3	3	2
89	0089	2	1	2	1	0	3	3	0	3	0	3	1	3	3	3	1	3	2	1	0	1	3	3	1	2	1	3	2	0	0	0	1	2	3	3	1	1	3	3	3	1	0	2	3	3	3	2	1	0	1	0	0
90	0090	2	3	0	0	0	0	1	1	2	3	0	0	3	1	3	0	3	1	2	3	0	1	3	1	2	2	0	3	0	3	1	3	3	3	3	2	3	0	1	2	1	0	1	2	1	0	1	0	2	1	1	1
91	0091	2	3	2	0	2	3	0	2	1	0	1	3	2	1	0	1	2	1	0	2	1	2	3	0	1	3	0	2	3	2	1	2	2	0	2	1	1	1	1	0	2	3	0	2	2	2	2	2	3	1	3	1
92	0092	3	1	0	2	2	3	1	3	3	0	1	2	2	1	2	2	0	1	1	3	1	1	2	1	3	0	0	2	3	3	3	1	0	0	3	0	3	0	0	3	0	1	1	2	1	0	2	3	3	2	2	0
93	0093	1	3	1	2	0	0	0	1	2	1	1	3	3	2	1	0	3	1	2	3	2	3	2	2	1	2	3	1	0	0	2	2	3	0	3	0	1	2	0	1	3	2	3	1	3	1	3	1	3	0	1	3
94	0094	0	0	1	1	1	0	0	1	3	1	3	3	2	1	0	2	0	1	1	0	3	2	3	0	3	2	2	1	1	3	3	3	2	3	3	1	0	0	3	1	1	2	1	1	3	0	2	0	3	1	2	1
95	0095	2	3	3	1	0	1	2	0	2	1	2	1	3	2	0	2	2	1	2	1	3	3	2	1	0	0	2	3	0	3	3	3	1	2	1	1	1	3	2	0	0	0	2	3	3	2	0	0	1	3	0	0
96	0096	2	0	1	1	1	3	3	0	2	2	1	1	3	2	0	3	0	3	2	2	0	3	0	2	2	1	2	1	3	0	1	3	3	1	0	2	1	3	1	0	3	1	3	1	1	0	0	1	1	2	3	2
97	0097	1	3	0	0	3	3	3	3	2	0	2	3	0	2	0	2	2	0	2	2	0	1	3	0	3	0	2	1	3	1	1	2	1	1	3	0	0	2	0	0	2	2	3	1	1	2	3	3	0	0	3	0
98	0098	0	2	0	1	2	0	3	0	0	1	2	1	1	2	0	1	0	2	3	0	0	0	2	1	2	3	1	3	0	2	1	3	1	2	3	0	3	0	2	3	1	3	1	1	3	0	0	3	3	1	2	0
99	0099	3	0	3	1	2	2	3	1	1	3	3	1	3	3	3	1	0	3	0	2	2	2	0	3	3	0	0	0	3	1	2	1	1	0	3	0	1	0	3	0	3	0	0	0	2	2	3	2	2	0	0	1
100	0100	1	1	3	3	0	1	2	3	1	3	3	2	3	3	2	1	0	0	3	0	3	0	3	1	1	0	1	1	1	1	2	2	3	0	1	3	0	1	2	0	1	3	2	3	0	3	2	3	3	2	0	1

[PeterClemmensen · Accepted solution]

Ah, I missed that. Then it is actually a lot simpler:

data have(drop=j);
   format ID;
   array i{52};
   do ID=1 to 1000;
      do j=1 to dim(i);
         i[j]=floor(4*rand('uniform'));
      end;
      output;
   end;
   format ID z4.;
run;

data want;
   set have;
   array iVars i1-i52;
   array idx idx1-idx48;
   if _N_<=20 then do until (cmiss(of iVars[*])=48);
      call missing(iVars[ceil(52*rand('uniform'))]);
   end;
   drop idx:;
run;

This should resolve both issue (1) and (2)..

Let me know if this works for you? 🙂

[TX_STAR]

Hi draycut,

It works perfect!

Thanks so much!

[PeterClemmensen]

Anytime. Glad to hear that it solved your problem 🙂