I am running an ordinal regression in SPSS, with a categorical predictor (9 neighbourhoods) and an ordinal dependent (satisfaction, with three levels: 1 '(very) satisfied' 2 'not satisfied, not unsatisfied' 3 '(very) unsatisfied'). I want to test whether living in a certain neighbourhood affects a person's satisfaction-score. My Parameter Estimates table in my SPSS Output looks like this
Estimate Sig Threshold satisfaction = 1 -,275 ,011 satisfaction = 2 ,355 ,001 Location neighbourhood1 -,822 ,000 neighbourhood2 ,418 ,024 neighbourhood3 -,047 ,795 neighbourhood4 -,622 ,001 neighbourhood5 -,636 ,001 neighbourhood6 -,285 ,123 neighbourhood7 -,595 ,000 neighbourhood8 -1,033 ,000 neighbourhood9 0
I am struggling with interpreting the estimates here. I have seen on several websites that the estimates are supposed to be interpreted the same way they would in 'normal' linear regression, in that "if a subject were to increase its neighbourhood1 score by one point, its ordered log-odds of being in a higher satisfaction category would decrease by 0,822 while the other variables in the model are held constant" (https://stats.idre.ucla.edu/spss/output/ordered-logistic-regression/). However, increasing the score on neighbourhood1 doesn't make sense, since a subject either lives there or does not. So how do I deduce the direction of the effect from this output? Am I even running the appropriate analysis? Help!
Furthermore, would it be necessary to maybe rescore the satisfaction-variable so that 1 denotes (very) unsatisfied and 3 means (very) satisfied?
Thanks a lot in advance!