View source: R/summary.flexsurvreg.R
normboot.flexsurvreg  R Documentation 
Produce a matrix of alternative parameter estimates under sampling
uncertainty, at covariate values supplied by the user. Used by
summary.flexsurvreg
for obtaining confidence intervals around
functions of parameters.
normboot.flexsurvreg(
x,
B,
newdata = NULL,
X = NULL,
transform = FALSE,
raw = FALSE,
tidy = FALSE,
rawsim = NULL
)
x 
A fitted model from 
B 
Number of samples. 
newdata 
Data frame or list containing the covariate values to
evaluate the parameters at. If there are covariates in the model, at least
one of 
X 
Alternative (less convenient) format for covariate values: a
matrix with one row, with one column for each covariate or factor contrast.
Formed from all the "model matrices", one for each named parameter of the
distribution, with intercepts excluded, 
transform 

raw 
Return samples of the baseline parameters and the covariate effects, rather than the default of adjusting the baseline parameters for covariates. 
tidy 
If 
rawsim 
allows input of raw samples from a previous run of

If newdata
includes only one covariate combination, a matrix
will be returned with B
rows, and one column for each named
parameter of the survival distribution.
If more than one covariate combination is requested (e.g. newdata
is
a data frame with more than one row), then a list of matrices will be
returned, one for each covariate combination.
C. H. Jackson chris.jackson@mrcbsu.cam.ac.uk
Mandel, M. (2013). "Simulation based confidence intervals for functions with complicated derivatives." The American Statistician (in press).
summary.flexsurvreg
fite < flexsurvreg(Surv(futime, fustat) ~ age, data = ovarian, dist="exp")
normboot.flexsurvreg(fite, B=10, newdata=list(age=50))
normboot.flexsurvreg(fite, B=10, X=matrix(50,nrow=1))
normboot.flexsurvreg(fite, B=10, newdata=list(age=0)) ## closer to...
fite$res
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