I am investigating unconscious racial prejudice as a predictor for guilty or not guilty judgements (Using SPSS).
I have a continuous variable for unconscious racial prejudice (higher numbers equal higher levels of racial prejudice), which I want to see if it can predict future judgements of guilt. My dependent variable is a scale where 0 = definately not guilty, and 100 = definately guilty. My sample is not normally distributed, as it clusters around 25 and 75, giving me a binomial distribution. (In other words people have on average been 50% confident in a guilty decision, or 50% confident in a not guilty decision. It was predicted that people would find it hard to decide and as such would have very low levels of confidence. I was wrong! My sample chose either guilty or not guilty in equal numbers, but they were all very confident in the decisions they made!)
Is there anyway of analysing my data? I note that binomial regressions and Ordinary Least Squares both need a dichotomous dependent variable. I can not just divide my group into 'guilty' or 'not guilty' as it is predicted that higher unconscious racial prejudice will predict higher levels of confidence in a guilty verdict, and lower levels of unconscious prejudice will lead to higher levels of confidence in a not guilty verdict.
If anyone could help it would be much appreciated. It's for my psychology honours thesis.