Hi Fay,
I think you might be much better off using PROC IML for what you're trying
to accomplish. If you are interested in getting an external data set into
an IML matrix, one simple way to do this is:
data x;
infile 'c:\imp1.txt';
input x1 x2;
proc iml;
use x;
read all var {x1 x2} into x;
run;
If after manipulating the matrix, you want to submit it to a different proc
(say to do EM), you could do something like this:
proc iml;
x = {1 1 1,
2 2 2,
3 3 3};
create dat from x[colname = {x1 x2 x3}];
append from x;
proc means data = dat;
var x1 x2 x3;
run;
If you're interesting in being able to refer to specific array elements,
that seems like the way to go. If it would help, contact me directly and I
can give you IML code I used for a couple recent missing data simulations.
They aren't exactly what you need, but you can probably alter snipets of the
code to fit your study.
Hope this helps,
Craig Enders
-----Original Message-----
From: Fay Hughes
To: [email protected]
Sent: 1/22/2003 12:22 AM
Subject: IMPUTE: SAS help required
Hi,
I am trying to programme several simple imputation techniques (namely
unconditional and conditional mean imputation, Healy-Westmacott
procedure, Buck's 1960 method as well as regression based methdos) as
well as using SAS to do EM and DA. My problem is that I want to read in
a completely observed data set and then randomly remove values, and then
use the dataset created for analyses. The way I am thinking of
programming requires my data set to be in an array format so that I can
work with the entire thing, individual values or columns by specifying
things like data, data[1,2] and data[1,*]. I amn having problems getting
SAS (see code below) to create arrays - any help on this problem,
possible SAS codes or places to look on the web for help would all be
appreciated.
Many thanks
Fay Hughes
Statistics masters student
University of Natal, Durban
SAS code (randomly removes values, but does not put the remaining ones
into an array)
data try;
input Oxygen RunTime RunPulse @@;
array try2(3,1) Oxygen RunTime RunPulse;
DO cols = 1 to 3;
DO rows = 1 to 1;
x=rand('uniform');
if (x<0.1) then try2(cols,rows)= 0;
end;
end;
datalines;
44.609 11.37 178
39.442 13.08 174
45.313 10.07 185
60.055 8.63 170
51.855 10.33 166
49.156 8.95 180
39.407 12.63 174
46.080 11.17 156
45.790 10.47 186
50.545 9.93 148
48.673 9.40 186
47.920 11.50 170
47.467 10.50 170
;
