So I have these 101 variables and they are all continious.  they are, say, v1 v2 v3 v4.....v100 yes_No. Now I wanted to seperate values on EACH VARIABLE to 10 groups.  for example, "age" for 10 groups,and "income" for 10 groups. One observation can be in group one for V1 and group 6 for V2. I know we can use proc rank to seperate out groups but I need help from there on. So, how do I do this on the 100 varibales? Any macro suggestions? What I mean is in the follwing, (Please ingonre any syntax errors, they are just to express my thoughts) do order=1 to 100; %let varlist=v1-v100; %macro xx (  , order ); data data_new; set data_old keep &order from varlist; run; proc rank data=data_new; groups=10; out=ranknew; run; data ranknew; iv&order= {count(yes_no=1)/ count(yes_no=0)} %mend xx; and hopefully I will have the 100 new dataset all combined together. Please help.  Thank you all very much in advance. updated: by the way extra question, how to write a program quickly detect/seperate out which variables are continuous which are discrete quickly and label them?  thanks. ... View more

Nothing statistics here. I have a table which is a similaroty matrix, and it looks like this, a b c a 1 0.8 0.7 b 0.8 1 0.2 c 0.7 0.2 1 I was hoping to do the following, and let tables become either Header 1 a a b b c c a 1 a 0.8 b 0.7 c b 0.8 a 1 b 0.2 c c 0.7 a 0.2 b 1 c or the transpose of it, doesn't matter. Header 1 a b a 1 0.8 a a a b 0.8 1 b b b As long as I have the original table by row or by column, seperated by one colume which is fullfilled by the "previous" column name or rowname. Please let me know how to do this.  Thank you very much. ... View more

I guess my problem is a little complex here.  I need to specify MISSING VALUES to be able to do IMPUTATION. SoI have a dataset with several variables and each of the variables has missing values, however they are coded in some ways. for example,  data one looks like this, vb1 vb2 vb3 1 b 4 1 a 1 2 a 1 3 c 3 2 b 2 actually, in vb1, "1" means missing; in vb2 "a" means messing and in vb3, "4" means missing and so on;  Those values means "missing", "unknown", "unspecified", so they are missings just they've been coded. I actually use proc sql to create a new table, and doing something like this, 1. data vb1_index; set one; input value $ value_d $; 1    . 2    1 3    2 ; run; 2. use "proc sql" to combine tables together But in the final results, sas looks at it like vb1 has "no missing values" with "3" (instead of 5) obsetrvations and same as for vb2, vb3...... in this way I have nothing missing since sas only looks at completed cases.  I used proc means n nmiss options to get the results.  so i don't know if my imputation is going to work well. please let me know a quick way to set those values as missing values because my "several" variables are like.....30+, thank you all very much!! ... View more