SPSS - two non-dichotomous categorical variables

[wannycang]

I'm having some issues running an analysis with two categorical variables that are both non-dichotomous...

Some background information on my study: My study focuses on how young adults sexually communicate in an online dating setting, and what influences them to do so. Participants are given a simulated online dating scenario where they see an online dater's profile (with a picture and a message), and then they are given the opportunity to reply to the profile.

What I'm having trouble with is analysing how the profile's message (sorted into 4 levels based on how 'sexy' it is) correlates to how the participants responds (also coded into 4 levels of how 'sexy' their response is). I hypothesise that the 'sexier' the profile's message is, the more 'sexy' the participant will respond. ​

So my two categorical variables are:
How sexy the profile's message is (4 levels)
How sexy the participants response is (4 levels)

What analysis should I run for this??

[Art Kendall]

If you are still in the design stage of you study I strongly suggest that you use more levels in your Ordinal/interval variables.  Since the underlying construct is continuous this would be a better operationalization of the construct.

If you are already have the data, start by doing a scatterplot of your variables.

If your levels are ordered your variables are at least ordinal.

ask for all statistics on CROSSTABS.  The output groups the coefficients by what they are useful for.

http://pic.dhe.ibm.com/infocenter/spssstat/v22r0m0/index.jsp?topic=%2Fcom.ibm.spss.statistics.help%2Fspss%2Fbase%2Fidh_xtab_statistics.htm

describes the coefficients.  

You would be interested in predicting your DV from your IV.

Are your results very different from assuming that the levels are interval, i.e., that the the intervals between the values are not very discrepant?  If you have CATREG available in your installation of SPSS you can actually compare the fits.