\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"), grid=FALSE,seqLength=300, type.relsurv=c("excess","total","other"), scale=365.24, rmap, ratetable=survival::survexp.us, se.fit=FALSE,link=NULL,exposed=incrVar(var),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"), grid=FALSE,seqLength=300, se.fit=FALSE,link=NULL,exposed=incrVar(var),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{"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 (defaults to incrementing ``var'')} \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)}