Sets parameters for logistf calls.
logistf.mod.control(tau = 0.5, terms.fit = NULL)Penalization parameter (default = 0.5)
A numeric vector of terms to fit. Intercept has to be included if needed.
data(sexagg)
fit2<-logistf(case ~ age+oc+vic+vicl+vis+dia, data=sexagg, weights=COUNT,
modcontrol=logistf.mod.control(terms.fit=c(1,2)))
summary(fit2)
#> logistf(formula = case ~ age + oc + vic + vicl + vis + dia, data = sexagg,
#> modcontrol = logistf.mod.control(terms.fit = c(1, 2)), weights = COUNT)
#>
#> Model fitted by Penalized ML
#> Coefficients:
#> coef se(coef) lower 0.95 upper 0.95 Chisq p
#> (Intercept) 0.3030238 0.1408917 -3.308572 3.748575 4.678807 0.03053694
#> age -0.8160945 0.3564077 -4.806455 1.635557 5.421096 0.01989486
#> oc 0.0000000 0.0000000 0.000000 0.000000 0.000000 0.00000000
#> vic 0.0000000 0.0000000 0.000000 0.000000 0.000000 0.00000000
#> vicl 0.0000000 0.0000000 0.000000 0.000000 0.000000 0.00000000
#> vis 0.0000000 0.0000000 0.000000 0.000000 0.000000 0.00000000
#> dia 0.0000000 0.0000000 0.000000 0.000000 0.000000 0.00000000
#> method
#> (Intercept) 2
#> age 2
#> oc 3
#> vic 3
#> vicl 3
#> vis 3
#> dia 3
#>
#> Method: 1-Wald, 2-Profile penalized log-likelihood, 3-None
#>
#> Likelihood ratio test=5.421096 on 1 df, p=0.01989486, n=239
#> Wald test = 7.081914 on 1 df, p = 0.007786578