Re-catorgorize data into new variables

[UGAstudent]

I'm trying to organize a continuous variable into smaller blocks. For example. Im using CD4 counts 1-1500. I want to break the CD4 count variable into smaller blocks for analyzation. 1-200 would be low CD4. 201-500 would be medium CD4 level and 501 and above would be high CD4 level. 

what code would I use to do this, if it could be done? 

[novinosrin]

Use proc format aka user defined format

This link might be of help-->

https://stats.idre.ucla.edu/wp-content/uploads/2016/02/bt3001.pdf

http://www2.sas.com/proceedings/sugi27/p056-27.pdf

[ballardw · Accepted solution]

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@UGAstudent wrote:

I'm trying to organize a continuous variable into smaller blocks. For example. Im using CD4 counts 1-1500. I want to break the CD4 count variable into smaller blocks for analyzation. 1-200 would be low CD4. 201-500 would be medium CD4 level and 501 and above would be high CD4 level. 

what code would I use to do this, if it could be done? 

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An example:

proc format library=work;
/* Format names cannot end in a digit to
   avoid confusion with display length options
*/
value cd4_
0  -  200 = 'Low'
200<- 500 = 'Medium'
500<-high = 'High'
;
run;

proc freq data=yourdata;
  tables cd4;
  format cd4 cd4_. ;
run;

Formats are very powerful tools as you can create multiple formats and use as needed. Almost all of the analysis procedures will honor groupings assigned in custom formats.

[UGAstudent]

This worked well. 

However, Im trying to do a linear regression but it says the newly created variables are not found? 

proc Reg data=Import;
title "Example of linear regression";
model Factor1 = Low;
run;

[PaigeMiller]

Low is not a variable. It is a formatted value.

If your goal is to do a regression on just the low values, none of the formatting is needed.

proc Reg data=Import(where=(0<=cd4<=200));
title "Example of linear regression";
model Factor1 = cd4;
run;

P.S.: It is always helpful to say what analysis you would like to do in your original post.