Ita.Cirovic-Donev@hypo-alpe-adria.com wrote:
I have the following output from the logistic regression:
Coef S.E. Wald Z P
Intercept -2.5159 0.3073 -8.19 0.0000
P4.t -0.4595 0.2080 -2.21 0.0272
P5.t -0.6054 0.2363 -2.56 0.0104
L5.t 0.9877 0.3665 2.70 0.0070
L12.t -1.6130 0.2577 -6.26 0.0000
L17.t -3.4368 0.2876 -11.95 0.0000
A1.t 0.4639 0.1906 2.43 0.0149
A7.t 1.1285 0.2482 4.55 0.0000
LEV21.t 1.1970 0.1887 6.34 0.0000
LEV23.t -1.7330 0.2511 -6.90 0.0000
these are financial variables, rank transformed prior to runing logistic
regression. My question is about the intercept. Is it normal for it to be
so large as compared to other variables. thanks
Ita
Why would you expect the variables to act on the log odds in a way that
is linear on the ranks? If you are concerned about linearity, then
regression splines may be the answer. If you are concerned about
robustness then curtailing the regression spline fits to extrapolate in
a flat fashion will deal with overly influential observations. You will
have difficulty getting predicted values when covariates are ranked.
Frank
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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