# Thread: Comparing Ordinal IV and Ordinal DV

1. ## Comparing Ordinal IV and Ordinal DV

Hey guys

another question

So I have set up this experiment about the effects of Virtual Surgical Planning on various aspects of outcomes of the procedure.

I need to figure out whether Virtual Surgical Planning has significant effects on "Flap Loss" (medical jargon for the skin graft to cover the wound was rejected or became necrotic and didn't survive the procedure).

I ALSO need to see if co-morbidities such as smoking, hypertension, diabetes, etc, had significant effects on flap loss as well.

So how I have my variables in SPSS set up is

VSP - ordinal
0 = did not receive VSP

This is my independent variable

Then I have

Flap Loss - ordinal
0 = no flap loss
1 = partial flap loss
2 = total flap loss

Hypertension - ordinal
0 = no hypertension
1 = hypertension

Tobacco - ordianl
0 = does not use tobacco
1 = uses tobacco

etc etc etc

So if I am trying to analyze my independent variable against one dependent variable at a time, what test would I run? Chi-square is giving me weird results, something due I think to the frequency being less than 5 for a lot of these variables. And I don't think I can do Kruskal-Wallace, if that would even be what I need to do.

So basically, comparing an ordinal independent variable against 1 ordinal dependent variable.

Any help would be greatly appreciated.

I attached my data sheet if you are interested (it's from SPSS but I just threw it into an Excel sheet)

2. ## Re: Comparing Ordinal IV and Ordinal DV

I would run binary logistic regression since your DV flap loss has two levels. You will run you IV as a dummy variable in this case. I would think your comorbidities such as smoking are independent variables not dependent ones since you appear to be interested in their effect on flap loss. But I may not understand your question.

3. ## The Following User Says Thank You to noetsi For This Useful Post:

mjbarteau (08-22-2013)

4. ## Re: Comparing Ordinal IV and Ordinal DV

Originally Posted by noetsi
I would run binary logistic regression since your DV flap loss has two levels. You will run you IV as a dummy variable in this case. I would think your comorbidities such as smoking are independent variables not dependent ones since you appear to be interested in their effect on flap loss. But I may not understand your question.
you know you are totally right

yes I also forgot to mention the flap loss has multiple levels

thanks for pointing that out, it's been a long day and this leg of my data crunching has really gotten to me

thanks!

5. ## Re: Comparing Ordinal IV and Ordinal DV

Okay so I ran the binary regression against basically all the DV's I have entered so far

I had to change "Flap Loss" to just 0 or 1. 1 meaning "partial or total flap loss"; when I had multiple levels to this DV it wouldn't let me do the regression.

ANYWAY

so this data looks like total crap right? Is that what this table at the bottom is saying? my sig is like astronomical...

It's just frustrating, my boss wants me to run all these tests but it's pretty apparent just from looking at it that there is nothing in the numbers, yet I have to keep digging

attached the regression output

again thank you so much

6. ## Re: Comparing Ordinal IV and Ordinal DV

Just a quick bump.... any other test that would be better?

I'm just getting gigantic numbers for my results

7. ## Re: Comparing Ordinal IV and Ordinal DV

You only have 3 events out of a total of 22 cases. Unfortunately this is not anywhere near enough to construct a meaningful regression model (a common rule of thumb is that you need 10 events, or non-events [whichever is lower], for each covariate in the model).

8. ## The Following User Says Thank You to bukharin For This Useful Post:

mjbarteau (08-25-2013)

9. ## Re: Comparing Ordinal IV and Ordinal DV

Awesome! thanks for the rule of thumb. As you can tell I'm pretty new to this

Thanks

 Tweet

#### Posting Permissions

• You may not post new threads
• You may not post replies
• You may not post attachments
• You may not edit your posts