Dear R list,

 

From the lrm() binary logistic model we derived the G2 value or the
likelihood-ratio chi-squared statistic given as L.R. model, in the output of
the lrm().

 

 

How can this value be penalized for non-linearity (we used splines in the
lrm function)?

 

lrm.iRVI <- lrm(arson ~ rcs(iRVI,5),
penalty=list(simple=10,nonlinear=100,nonlinear.interaction=4)) 

 

This didn’t work properly.

 

 

The aim is to obtain a value that can be used to compare the goodness of fit
of the different univariate binary logistic models. 

 

(The lower the value, the better the fit)

 

 

Kind regards,

Jan

____________________________________________________________________
Ir. Jan Verbesselt
Research Associate
Group of Geomatics Engineering
Department Biosystems ~ Mł-BIORES
Vital Decosterstraat 102, 3000 Leuven, Belgium
Tel: +32-16-329750   Fax: +32-16-329760
http://gloveg.kuleuven.ac.be/
_______________________________________________________________________

 


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