P-values and confidence intervals for parameters in linear transformation models obtained from by the score test principle
score_test(object, ...)
# S3 method for tram
score_test(object, parm = names(coef(object)),
alternative = c("two.sided", "less", "greater"), nullvalue = 0,
confint = TRUE, level = .95, Taylor = FALSE, maxsteps = 25, ...)
an object of class tram
a vector of names of parameters to be tested.
These parameters must be present in object
.
a character string specifying the alternative hypothesis,
must be one of "two.sided"
(default), "greater"
or "less"
.
a number specifying an optional parameter used to form the null hypothesis.
a logical indicating whether a confidence interval should be
computed. Score confidence intervals are computed by default. A
1st order Taylor approximation to the Score statistc is used with
Taylor = TRUE
(in case numerical inversion of the score
statistic fails, Wald confidence intervals relying from this approximation are
returned).
the confidence level.
a logical requesting the use of a 1st order Taylor approximation when inverting the score statistic.
number of function evaluations when inverting the score statistic for computing confidence intervals.
additional arguments, currently ignored.
An object of class htest
or a list thereof. See Coxph
for an example. A corresponding permutation test for parameters in a
transformation models is available in
perm_test
.
Score tests and confidence intervals for the parameters in the linear
predictor of object
are computed. These parameters must be present
in object
.