Re: Deriving Formula from Ordinal Regression Results to Classify New Cases?

Posted by Vik Rubenfeld on
URL: http://spssx-discussion.165.s1.nabble.com/Deriving-Formula-from-Ordinal-Regression-Results-to-Classify-New-Cases-tp5715848p5715993.html

This is fantastic. I have almost got it.

In the ucla data set, the variables pared and public have just two levels, and so they get only one parameter estimate each.  Some of the variables in my data set have 5 levels, and so get 4 parameter estimates each, one for each level minus the highest level.  Here are the parameter estimates for a test run using two predictor variables:

PLUM Q7 BY Q5_3 Q5_4
  /LINK=LOGIT
  /PRINT=PARAMETER SUMMARY
  /SAVE=ESTPROB.



What is the correct way to apply this line of the algorithm:

   compute #eta0_subj1 = 2.203323 - (1.047664*0 + (-0.058683)*0 +
0.615746*3.260000).

...for predictor variables that have more than one parameter estimate?  In other words, which of the four possible parameter estimates is to be used?  I would have thought it would be the one that matches the observed value of the predictor variable for each case - but if the observed value is the highest possible value, then there is no matching parameter estimate. What am I missing?

I am attaching the test data set used in this example.

test-data.sav