Usage
logistfplot(formula = attr(data, "formula"), data = sys.parent(), which, pitch = 0.05, limits,
alpha = 0.05, firth = TRUE,
legends = TRUE, weights, control, plcontrol)Arguments
formula
a formula object, with the response on the left of the operator, and the
model terms on the right. The response must be a vector with 0 and 1 or FALSE and
TRUE for the model outcome, where the higher value (1 or TRUE) is modeled. It's possible
data
a data.frame where the variables named in the formula can be found, i. e.
the variables containing the binary response and the covariates.
which
a righthand formula specifying the plotted parameter, interaction or
general term, e.g. ~ A - 1 or ~ A : C - 1. The profile likelihood of the
intercept would be obtained by the formula ~ - ..
pitch
distances between the interpolated points in standard errors of
the parameter estimate, the default value is 0.05.
limits
vector of the minimum and the maximum on the x-scale in standard
deviations distant form the maximum likelihood. The default values
are the extremes of both confidence intervals, Wald and PL, plus or minus half a
standard deviation of the p
alpha
the significance level (1-$\alpha$ the confidence level,
0.05 as default).
firth
use of Firth's (1993) penalized maximum likelihood (firth=TRUE, the default) or the
standard maximum likelihood method (firth=FALSE) for the logistic regression. Note
that by specifying pl=TRUE and fi
legends
if FALSE, legends in the plot would be omitted
(default is TRUE).
control
a logistf.control object to define parameters for the Newton-Raphson iteration.
plcontrol
a logistpl.control object to define parameters for the Newton-Raphson iteration to estimate profile likelihood CLs.