The following program reads 14 family history variables (fhx1, ..., fhx14) arising from five subjects and stores the data in a one-dimensional array called edit. Then, SAS searches the edit array to determine whether or not any data values are missing. Fourteen (14) status variables (stat1, ..., stat14) are created to correspond to each of the 14 data variables. The status (1 if missing and 0 if nonmissing) is stored in another one-dimensional array called status:

DATA fhx;
	input subj v_date mmddyy8. fhx1-fhx14;
	array edit(14) fhx1-fhx14;
	array status(14) stat1-stat14;
	do i = 1 to 14;
		status(i) = 0;
		if edit(i) = . then status(i) = 1;
	end;
	DATALINES;
220004  07/27/93  0  0  0  .  8  0  0  1  1  1  .  1  0  1
410020  11/11/93  0  0  0  .  0  0  0  0  0  0  .  0  0  0
520013  10/29/93  0  0  0  .  0  0  0  0  0  0  .  0  0  1
520068  08/10/95  0  0  0  0  0  1  1  0  0  1  1  0  1  0
520076  08/25/95  0  0  0  0  1  8  0  0  0  1  1  0  0  1
;
RUN;
 
PROC PRINT data = fhx;
	var fhx1-fhx14;
	TITLE 'The FHX data itself';
RUN;
 
PROC PRINT data = fhx;
	var stat1-stat14;
	TITLE 'The presence of missing values in FHX data';
RUN;

Output

The first ARRAY statement tells SAS to group the fourteen family history variables, fhx1, ..., fhx14, into a one-dimensional array called edit. The second ARRAY statement tells SAS to group the fourteen status variables, stat1, ..., stat14, into a one-dimensional array called status. The DO loop tells SAS to review the contents of the 14 variables and to assign each element of the status array a value of 0 ("status(i) = 0"). If the element of the edit array is missing, however, then SAS is told to change the element of the status array from a 0 to a 1 ("if edit(i) = . then status(i) = 1").

Launch and run   the SAS program. Then, review the output from the PRINT procedures to convince yourself that the program does indeed do as described.

The previous program was written merely as a prelude to this example, in which the code is modified to illustrate the use of two-dimensional arrays. This program performs exactly the same task as the previous program, namely searching a subset of family history data for missing values. Here, though, we use one two-dimensional array called edit instead of two one-dimensional arrays:

DATA fhx2;
	input subj v_date mmddyy8. fhx1-fhx14;
	array edit(2,14) fhx1-fhx14 stat1-stat14;
	do i = 1 to 14;
		edit(2,i) = 0;
		if edit(1,i) = . then edit(2,i) = 1;
	end;
	DATALINES;
220004  07/27/93  0  0  0  .  8  0  0  1  1  1  .  1  0  1
410020  11/11/93  0  0  0  .  0  0  0  0  0  0  .  0  0  0
520013  10/29/93  0  0  0  .  0  0  0  0  0  0  .  0  0  1
520068  08/10/95  0  0  0  0  0  1  1  0  0  1  1  0  1  0
520076  08/25/95  0  0  0  0  1  8  0  0  0  1  1  0  0  1
;
RUN;
 
PROC PRINT data = fhx2;
	var fhx1-fhx14;
	TITLE 'The FHX2 data itself';
RUN;
 
PROC PRINT data = fhx2;
	var stat1-stat14;
	TITLE 'The presence of missing values in FHX2 data';
RUN;

Output

First, if you compare this program with the previous program, you should notice that the two programs have more similarities than differences. Here, we have just one ARRAY statement that defines the two-dimensional array edit containing 2 rows and 14 columns. The ARRAY statement tells SAS to group the family history variables (fhx1, ..., fhx14) into the first dimension and to group the status variables (stat1, ..., stat14) into the second dimension. Then, the DO loop tells SAS to review the contents of the 14 variables and to assign each element of the status dimension a value of 0 ("edit(2,i) = 0;"). If the element of the edit dimension is missing, however, then SAS is told to change the element of the status dimension from a 0 to a 1 ("if edit(1,i) = . then edit(2,i) = 1").

Launch and run   the SAS program. Then, review the output from the PRINT procedures to convince yourself that the program accomplishes using one two-dimensional array just as the previous program accomplished using two one-dimensional arrays.