I would like to regress the influence of income, education, marital status etc. on life satisfaction. The data I use is from the SHARE survey – life satisfaction can take values of 1–10, most values are around 6–8.
OLS regression seems to be a poor choice to me, as it might produce predicted values outside the 1–10 interval.
My colleagues have suggested that I might take a look at truncated/censored analysis, such as tobit regression. However, I do not believe that I have data which is censored in the way tobit regression would assume, which would be the case if only part of the real spectrum of values can be observed.
Most researchers use ordered logistic regression. This seems valid to me, but 10 might be quite high number of possible outcomes for ologit (I have usually done it with fewer outcomes, though I am not sure if this is an issue at all), and I believe ologit does not assume the intervals between the categories to be of equal size (stated here), which I however believe is the case in my scenario (why would the difference between 3 and 4 be any different than between 7 and 8?)
I wonder if interval regression is what I need. I think it is, but I need proof :)
So, which statistic analysis would you recommend?