I am conducting research investigating two different groups of women: one group of Short-Stature Women (SSW) and another with Non-Short Women (NSW). We have the hypothesis that SSW has an inaccurate auto-perception of their current body size (CBS). We assessed CBS with a figure rating scale, consisting of 9 different silhouettes, ranging from 1 to 9 (which would assess something like from "malnourished" to "very obese"). We know that CBS is highly determined by the person's Body Mass Index (BMI). Hence, we would like to know if the BMI is a significantly better "predictor" of CBS in NSW compared to SSW.
My first approach was to run two Spearman rho rank correlation test (one for each group (SSW and NSW), between BMI and CBS) and then to compare both coefficients using the Fisher's Z-test. Nevertheless, I am pretty sure that I can treat CBS as an ordinal variable, right? So, it seems to me like an ordinal regression (using CBS as DV and BMI as IV) would be more suitable to my data. If this is true, my problem is that I do not know how to compare coefficients for ordinal regression. Would it be comparing Nagelkerke-R²? How can I do this?
To summarize I have 2 main questions: a) Is Spearman rho rank correlation with comparison of the coefficients by Fisher's Z-test adequate in this case? and b) If ordinal regression is more adequate, how can I compare the coefficients of the regression between my two groups?