BookmarkSubscribeRSS Feed
🔒 This topic is solved and locked. Need further help from the community? Please sign in and ask a new question.
karen8169
Obsidian | Level 7
proc IML;
agegroup = {"<=34",">34"};
status = {"Single" "Married" "Divorced"};
counts ={25 15 0,
               2 9 3};
p = counts / sum(counts);
print p[colname=status
           rowname=agegroup
		   label="Marital Status  by Age Group"
		   format=percent7.1];

proc freq data=counts order=data;
   tables agegroup*status / expected cellchi2 norow nocol chisq;
   output out=ChiSqData n nmiss pchi lrchi;
   weight Count;
   title 'Chi-Square Tests for 3 by 5 Table of Eye and Hair Color';
run;

proc print data=ChiSqData noobs;
   title1 'Chi-Square Statistics for agegroup and status';
   title2 'Output Data Set from the FREQ Procedure';
run;
proc freq 
    agegroup = {"<=34",">34"};
    status = {"Single" "Married" "Divorced"};
    counts ={25 15 0,
               2 9 3};
     tables agegroupr *status 
          / chisq;

     weight counts;
run;

 I have found two code of independence test. But the form of original data,first passage, is not the same with the data which I have found. So who can tell me how to correct one of them or both.

1 ACCEPTED SOLUTION

Accepted Solutions
Rick_SAS
SAS Super FREQ

The first set of statement in PROC IML do not run any tests. They just print the proportions for a table.

 

The second set of statement require a SAS data set called COUNTS that contains the data. The code runs some tests for association on that data, but be warned that the chi-square test is not recommended for tables with small cell counts.

 

The third set of statements doesn't make sense and is not valid.

 

Perhaps the following DATA set and PROC FREQ statement will help get you started:

data counts;
length agegroup $5. status $10.;
input agegroup $ status $ count;
datalines;
Young Single    25
Young Married   15
Young Divorced   0
Older Single     2
Older Married    9
Older Divorced   3
;

proc freq data=counts order=data;
   tables agegroup*status / norow nocol chisq;
   weight Count;
run;

View solution in original post

2 REPLIES 2
Rick_SAS
SAS Super FREQ

The first set of statement in PROC IML do not run any tests. They just print the proportions for a table.

 

The second set of statement require a SAS data set called COUNTS that contains the data. The code runs some tests for association on that data, but be warned that the chi-square test is not recommended for tables with small cell counts.

 

The third set of statements doesn't make sense and is not valid.

 

Perhaps the following DATA set and PROC FREQ statement will help get you started:

data counts;
length agegroup $5. status $10.;
input agegroup $ status $ count;
datalines;
Young Single    25
Young Married   15
Young Divorced   0
Older Single     2
Older Married    9
Older Divorced   3
;

proc freq data=counts order=data;
   tables agegroup*status / norow nocol chisq;
   weight Count;
run;

karen8169
Obsidian | Level 7

Can I ask the meaning of " order= data" and " weight Count" ? I've consulted the directions but still confused.

Ready to join fellow brilliant minds for the SAS Hackathon?

Build your skills. Make connections. Enjoy creative freedom. Maybe change the world. Registration is now open through August 30th. Visit the SAS Hackathon homepage.

Register today!
How to Concatenate Values

Learn how use the CAT functions in SAS to join values from multiple variables into a single value.

Find more tutorials on the SAS Users YouTube channel.

Click image to register for webinarClick image to register for webinar

Classroom Training Available!

Select SAS Training centers are offering in-person courses. View upcoming courses for:

View all other training opportunities.

Discussion stats
  • 2 replies
  • 894 views
  • 2 likes
  • 2 in conversation