BookmarkSubscribeRSS Feed
Roxxanne
Fluorite | Level 6

Hello,

I am struggling to determine the correct code and/or procedure for my dataset. My dependent variable (i.e. Equity_1L) is discrete and not normally distributed. I have multiple categorical independent variables (i.e. age, sex, education, income, relationship, cancer and healthcare - only cancer and healthcare are dichotomous, the others have multiple levels). My main analysis was to determine whether the median value of my dependent variable differed from a known value. I completed this and wanted to check for correlations, after doing some research, I determined that an ordinal regression analysis would be the best fit for my data. I attempted this code and received an error:

proc logistic data=WORK desc;

model Equity_1L = Age Sex Education Income Relationship Cancer Healthcare;
run;

The error stated my variables need to be either numeric or specified by a class statement, so I moved all non-dichotomous to the class statement:

proc logistic data=WORK.THESIS desc;
model Equity_1L = Cancer Healthcare;
class Age Sex Education Income Relationship;
run;

I still receive an error saying the same thing. Basically, I am unsure if I am suppose to re-code these variables as dummy variables or try a different analysis. I did perform a 1 on 1 Wilcoxon analysis with each independent variable with my dependent variable to check for correlations however, I wasn't sure if this was the proper way to do it, as I thought all correlations should be checked for at once (just in case there are interactions). Thank you for your help!

1 REPLY 1
Rick_SAS
SAS Super FREQ

Put the CLASS statement before the MODEL statement.

hackathon24-white-horiz.png

The 2025 SAS Hackathon has begun!

It's finally time to hack! Remember to visit the SAS Hacker's Hub regularly for news and updates.

Latest Updates

What is ANOVA?

ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 1 reply
  • 623 views
  • 3 likes
  • 2 in conversation