Sets parameters for modified Newton-Raphson iteration for finding profile likelihood confidence intervals in Firth's penalized likelihood logistic regression
logistpl.control(
maxit = 100,
maxhs = 0,
maxstep = 5,
lconv = 1e-05,
xconv = 1e-05,
ortho = FALSE,
pr = FALSE
)The maximum number of iterations
The maximum number of step-halvings in one iteration. The increment of the beta vector within one iteration is divided by 2 if the new beta leads to a decrease in log likelihood.
Specifies the maximum step size in the beta vector within one iteration.
Specifies the convergence criterion for the log likelihood.
Specifies the convergence criterion for the parameter estimates.
specifies if orthogonalization is requested.
specifies if rotation is requested
The maximum number of iterations
The maximum number of step-halvings in one iteration. The increment of the beta vector within one iteration is divided by 2 if the new beta leads to a decrease in log likelihood.
Specifies the maximum step size in the beta vector within one iteration. Set to -1 for infinite stepsize.
Specifies the convergence criterion for the log likelihood.
Specifies the convergence criterion for the parameter estimates.
Requests orthogonalization of variable for which confidence intervals are computed with respect to other covariates
Request rotation of the matrix spanned by the covariates
Georg Heinze
logistpl.control() is used by logistf to set control parameters to default values
when computing profile likelihood confidence intervals.
Different values can be specified, e. g., by logistf(..., control= logistf.control(maxstep=1)).
data(sexagg)
fit2<-logistf(case ~ age+oc+vic+vicl+vis+dia, data=sexagg, weights=COUNT,
plcontrol=logistpl.control(maxstep=1))
summary(fit2)
Run the code above in your browser using DataLab