Hi ,
I am running Proc Logoctics procedure.I got the message "Ridgin failed to improve the likelihood function". I changed the option ridging = absolute and this also gave the same message.
With Ridging = none , the no. of iteration increased , but still the model ended with same warnning . This time the message was to use halfmax=option and increase no. of steps oe specify a new set of initial parameter estimates using INEST option. What does this mean?.
I have 26 predictor variables in the model , is this because of large no. of variables. If so then how do we reduce the variables.
Vishal
As already pointed out, this is probably a data issue.
I encountered the same warning and for me the problem was so-called perfect separation (a lot can be found by simply googling this term). Loosely explained, this means that for a certain categorical variable, one or more categories / groups only have data for either your success or non-success group.
For example:
Variable color that can take on Blue, red, yellow.
Y = 1 (success): Blue 100, red 50, yellow 50
Y = 0 (fail / non-success): Blue = 50, red = 100, yellow = 0
For the Yellow group, there are only successes.
HTH
It is not really possible to know exactly what caused this, but you can try various combinations of the TECH= and RIDGING= options. You could also try using the FIRTH option which maximizes a penalized likelihood. Since you have a fair number of predictors, you might be flirting with separation issues, so the the FIRTH option might help. Also you could consider using a model selection method (but don't use BACKWARD). The more modern Lasso method is available in PROC HPGENSELECT.
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