Solved
New Contributor
Posts: 3

# Test significant differences between two group proportions using a non-binary categorical variable

Hi,

I have a data set with a pass/fail variable and would like to test for significant differences between these proportions by gender (M/F). The reason I am unsure about how to proceed with this analysis is because the pass/fail variable has three levels (fail below/ pass/ fail above). I have two questions:

1) Is there a test appropriate for determining statistically significant differences between two groups when the proportion being tested is not binary?

2) Taking it a step further, is there a way to test differences between each level (e.g. comparing the proportion of males who failed below with the proportion of females who failed below)?

Thanks!
Dominique

Accepted Solutions
Solution
‎04-10-2018 03:59 PM
Posts: 3,039

## Re: Test significant differences between two group proportions using a non-binary categorical variab

1. Use the Chi-Squared test in PROC FREQ

2. Use the Chi-Squared test in PROC FREQ

--
Paige Miller

All Replies
Frequent Contributor
Posts: 87

## Re: Test significant differences between two group proportions using a non-binary categorical variab

Hey,

1. I would suggest you read this article about statistically significant and determin your own level as needed.
2. Well you could easily divide failed males by failed famles and great a measure that way
Solution
‎04-10-2018 03:59 PM
Posts: 3,039

## Re: Test significant differences between two group proportions using a non-binary categorical variab

1. Use the Chi-Squared test in PROC FREQ

2. Use the Chi-Squared test in PROC FREQ

--
Paige Miller
SAS Employee
Posts: 386

## Re: Test significant differences between two group proportions using a non-binary categorical variab

See this note - particularly the last section and the note it links to regarding multiple comparisons.

PROC Star
Posts: 404

## Re: Test significant differences between two group proportions using a non-binary categorical variab

Posted in reply to StatDave_sas

I can't quite make sense of your 3-level response ("three levels (fail below/ pass/ fail above")  but perhaps it might be considered to be ordinal. If so, use your favorite internet search tool for "ordinal logistic regression sas" for approaches that specifically account for an ordered response, as opposed to a nominal (unordered) multinomial response.

☑ This topic is solved.

Need further help from the community? Please ask a new question.

Discussion stats
• 4 replies
• 176 views
• 0 likes
• 5 in conversation