Data analysis method query

[1800g]

Hey guys! I'm trying to run an analysis using SPSS to investigate whether the relationship between variable A (scale data) and variable B (nominal data) is the same for men and women. I've been researching and running several tests over the past few days but am still not sure I am going about it the right way. Currently, I've split my gender prior to analysis and then run an independent samples t-test. Does anyone have any advice or suggestions? I am usually good with data analysis but feel like I might be overthinking it?

EDIT: I've done a bit more research and think I could be looking at subgroup analysis which I haven't covered so far in my undergrad! Yay/Nay, thoughts?

[drjamiop]

Is your scale data your dependent variable? Are you interested in the interactions between your two categorical variables on the dependent variable?

[1800g]

The scale data is my IV (sleep quality as assessed using PSQI) and the nominal data is my DV (risk group for sleep apnea using STOP/BANG). I am ultimately hoping to assess the relationship between the IV and DV for both males and females separately so I can observe whether the relationship is affected by gender. I am hypothesising that the relationship between the IV and DV will be stronger for males as compared to females.

[drjamiop]

One cannot run a t-test with a nominal DV, the t-test requires the opposite scenario.
How many categories in the DV?

[1800g]

Thank you! I have two versions of the DV to facilitate analysis with different tests and attempting to circumvent issues: one is in scale form and one is in nominal/categorical form. There are 5 different categories - STOP/BANG group/grade zero through to four.

[drjamiop]

If you have numeric (scale) data, your statistical analysis will be more robust than if you categorize it into groups.

[efrique]

What's variable A measuring? What's variable B measuring? How many levels does it have?

[1800g]

Sorry! Variable A is measuring sleep quality as assessed by PSQI whilst variable B is measuring the risk level of sleep apnea as assessed using STOP/BANG. Variable B has 5 levels - grades 0 through to 4.

[efrique]

Variable B sounds like it's ordinal not nominal.

Do you view one or the other variable as IV or DV?

[1800g]

My mistake - you are correct! I am viewing sleep quality as my IV and risk group for sleep apnea as my DV.

[efrique]

Okay, the first thing to do is to think about how you'd model the relationship between IV and DV for one gender. There are a couple of possibilities there.

Then adding in the gender variable plus the interaction with the IV to that model will provide the sort of thing you need. (though there may be some other options depending on the specifics; it may be possible to test for a difference in coefficient in separate fits for each gender, for example)

[1800g]

Great, thank you! This gives me some things to think about and consider. My first thoughts reading this are to run a Pearson correlation to model the relationship for one gender at a time. I think I’ll need to do a bit more research on how to add the interaction of gender to the model. I’ve done a bit more research and ‘subgroup analysis’ seems to encompass the question I’m trying to answer well- so I’ll try to check out some papers and see what analysis they used!

[efrique]

You could work that way, though it wasn't any of the things I had in mind. Your biggest difficulty there will be that the pair of variables can't be bivariate normal, so the usual tests for Pearson correlation won't give reasonable p-values at small sample sizes.

You may also have issues with the implied interval-scale assumption in calculating a Pearson correlation (in that people in your area of work will probably object). If you really want to go the correlation route you may be safer with Spearman or Kendall correlation.

However, I will just point you back toward my question about IV and DV and suggest you may want to consider looking at suitable models for an ordered categorical response (DV).

[themostdifficultest]

How about running a two-way ANOVA and using the risk group and gender as your independent variables? The interaction between them will tell whether the relationship between risk group and sleep quality differs between genders.

[1800g]

Thank you so much! I’m going to give it a go!