I need to compare proportions of difference scores between 2 (unequal n) samples (males vs. females) on 2 different measures. I want to enter the difference scores into contingency table for chi-square type analysis.
I subtract male-female scores for each of the 2 measures
R1C1 = Male"Yes"MeasureA - Female"Yes"MeasureA R1C2 = Male"Yes"MeasureB - Female"Yes"MeasureB R2C1 = Male"No"MeasureA - Female"No"MeasureA R2C2 = Male"No"MeasureB - Female"No"MeasureB
When I use this method for getting difference scores, not surprisingly, some values are negative, which prevents me from doing chi-square. Is there a way to transform the data to do away with the negative values but preserve the proportions? For example, I was wondering if it would be acceptable to just square all difference scores, and then do chi-square?
So here's a bit more detail. I am investigating a measure of sexual experiences. The original measure asks respondents to indicate whether or not they've experienced a variety of sexual encounters. The survey has 2 parallel versions -- one for females (asking about sexual victimization) and one for males (asking about perpetration). research has shown that, when given the original measure, females indicate ~2/3s increased rates of victimization, than males reported rate of perpetration. I have created a modified version of the survey (for both male and female versions) and I have hypothesized that this modified version will decrease the discrepancy rate between female/victims and male/perpetrators rates of responding.
I have an unequal number of males and females. each participant was given both versions of the survey (original and modified), the original was given first. I have collapsed the response data to be dichotimous -- so either "yes" ([female]i have been raped/[male]i have raped someone) or "no" ([female]i have never been raped/[male]i have never raped anyone).
So, what i need is a way to determine if the male-female discrepancy ratio on the original measure is significantly different from the male-female discrepancy ratio of the modifed version.
further additional info. I have already run paired sample t-tests and determined that male report rates on the modified versin are significantly higher than on the original -- female report rates are not significantly different across versions. So i know that the discrepancy is reduced (because male reports increased and females did not) but I'm looking for a direct way to compare the difference scores/proportions between measures.