Revision 45536c5580212aeb43a1cdf1a690e92cc843203c authored by Mark Clements on 07 January 2023, 02:40:02 UTC, committed by cran-robot on 07 January 2023, 02:40:02 UTC
1 parent b58cc9c
predict-methods.Rd
\name{predict-methods}
\docType{methods}
\alias{predict-methods}
\alias{predict,stpm2-method}
\alias{predict,pstpm2-method}
\title{ Predicted values for an stpm2 or pstpm2 fit}
\description{
Given an \code{stpm2} fit and an optional list of new data, return predictions
}
\section{Methods}{
\describe{
\item{object= "stpm2"}{an \code{stpm2} fit}
}}
\usage{
\S4method{predict}{stpm2}(object, newdata=NULL,
type=c("surv","cumhaz","hazard","density","hr","sdiff",
"hdiff","loghazard","link","meansurv","meansurvdiff","meanhr",
"odds","or","margsurv","marghaz","marghr","meanhaz","af",
"fail","margfail","meanmargsurv","uncured","rmst","probcure",
"lpmatrix", "gradh", "gradH","rmstdiff"),
grid=FALSE,seqLength=300,
type.relsurv=c("excess","total","other"), scale=365.24,
rmap, ratetable=survival::survexp.us,
se.fit=FALSE,link=NULL,exposed=NULL,var=NULL,
keep.attributes=FALSE, use.gr=TRUE,level=0.95,
n.gauss.quad=100,full=FALSE,...)
\S4method{predict}{pstpm2}(object, newdata=NULL,
type=c("surv","cumhaz","hazard","density","hr","sdiff",
"hdiff","loghazard","link","meansurv","meansurvdiff","meanhr",
"odds","or","margsurv","marghaz","marghr","meanhaz","af",
"fail","margfail","meanmargsurv","rmst","lpmatrix",
"gradh", "gradH","rmstdiff"),
grid=FALSE,seqLength=300,
se.fit=FALSE,link=NULL,exposed=NULL,var=NULL,
keep.attributes=FALSE, use.gr=TRUE,level=0.95,
n.gauss.quad=100,full=FALSE,...)
}
\arguments{
\item{object}{an \code{stpm2} or \code{pstpm2} object}
\item{newdata}{optional list of new data (required if type in
("hr","sdiff","hdiff","meansurvdiff","or","uncured")). For type in
("hr","sdiff","hdiff","meansurvdiff","or","af","uncured"), this defines the unexposed
newdata. This can be combined with \code{grid} to get a
regular set of event times (i.e. newdata would \emph{not}
include the event times). }
\item{type}{specify the type of prediction:
\itemize{
\item{"surv"}{survival probabilities}
\item{"cumhaz"}{cumulative hazard}
\item{"hazard"}{hazard}
\item{"density"}{density}
\item{"hr"}{hazard ratio}
\item{"sdiff"}{survival difference}
\item{"hdiff"}{hazard difference}
\item{"loghazard"}{log hazards}
\item{"meansurv"}{mean survival}
\item{"meansurvdiff"}{mean survival difference}
\item{"odds"}{odds}
\item{"or"}{odds ratio}
\item{"margsurv"}{marginal (population) survival}
\item{"marghaz"}{marginal (population) hazard}
\item{"marghr"}{marginal (population) hazard ratio}
\item{"meanhaz"}{mean hazard}
\item{"meanhr"}{mean hazard ratio}
\item{"af"}{attributable fraction}
\item{"fail"}{failure (=1-survival)}
\item{"margfail"}{marginal failure (=1-marginal survival)}
\item{"meanmargsurv"}{mean marginal survival, averaged over the
frailty distribution}
\item{"uncured"}{distribution for the uncured}
\item{"rmst"}{restricted mean survival time}
\item{"rmstdiff"}{restricted mean survival time difference}
\item{"probcure"}{probability of cure}
\item{"lpmatrix"}{design matrix}
}
}
\item{grid}{whether to merge newdata with a regular sequence of event
times (default=FALSE)}
\item{seqLength}{length of the sequence used when \code{grid=TRUE}}
\item{type.relsurv}{type of predictions for relative survival models:
either "excess", "total" or "other"}
\item{scale}{scale to go from the days in the \code{ratetable} object
to the analysis time used in the analysis}
\item{rmap}{an optional list that maps data set names to the ratetable
names. See \code{survexp}}
\item{ratetable}{a table of event rates used in relative survival when
\code{type.relsurv} is "total" or "other"}
\item{se.fit}{whether to calculate confidence intervals (default=FALSE)}
\item{link}{allows a different link for the confidence interval
calculation (default=NULL, such that
switch(type,surv="cloglog",cumhaz="log",hazard="log",hr="log",sdiff="I",
hdiff="I",loghazard="I",link="I",odds="log",or="log",margsurv="cloglog",
marghaz="log",marghr="log"))}
\item{exposed}{a function that takes newdata and returns a transformed
data-frame for those exposed or the counterfactual. By default, this increments \code{var} (except for cure
models, where it defaults to the last event time).}
\item{var}{specify the variable name or names for the
exposed/unexposed (names are given as characters)}
\item{keep.attributes}{Boolean to determine whether the output should
include the newdata as an attribute (default=TRUE)}
\item{use.gr}{Boolean to determine whether to use gradients in the
variance calculations when they are available (default=TRUE)}
\item{level}{confidence level for the confidence intervals (default=0.95)}
\item{n.gauss.quad}{number of Gauassian quadrature points used for
integrations (default=100)}
\item{full}{logical for whether to return a full data-frame with
predictions and \code{newdata} combined. Useful for
\code{lattice} and \code{ggplot2} plots. (default=FALSE)}
\item{\dots}{additional arguments (for generic compatibility)}
}
\value{
A data-frame with components \code{Estimate}, \code{lower} and
\code{upper}, with an attribute "newdata" for the \code{newdata}
data-frame.
}
\details{
The confidence interval estimation is based on the delta method using
numerical differentiation.
}
\seealso{\code{\link{stpm2}}}
\keyword{methods}
%%\keyword{ ~~ other possible keyword(s)}
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