predict-methods: Predicted values for an stpm2 or pstpm2 fit

Description

Given an stpm2 fit and an optional list of new data, return predictions

Usage

# S4 method for stpm2
predict(object, newdata=NULL,
               type=c("surv","cumhaz","hazard","density","hr","sdiff",
               "hdiff","loghazard","link","meansurv","meansurvdiff",
               "odds","or","margsurv","marghaz","marghr","meanhaz","af",
               "fail","margfail","meanmargsurv","uncured"),
               grid=FALSE,seqLength=300,
               se.fit=FALSE,link=NULL,exposed=incrVar(var),var,
               keep.attributes=TRUE, use.gr=TRUE,...)
    # S4 method for pstpm2
predict(object, newdata=NULL,
               type=c("surv","cumhaz","hazard","density","hr","sdiff",
               "hdiff","loghazard","link","meansurv","meansurvdiff",
               "odds","or","margsurv","marghaz","marghr","meanhaz","af",
               "fail","margfail","meanmargsurv"),
               grid=FALSE,seqLength=300,
               se.fit=FALSE,link=NULL,exposed=incrVar(var),var,
               keep.attributes=TRUE, use.gr=TRUE,...)

Arguments

object

an stpm2 or pstpm2 object

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 grid to get a regular set of event times (i.e. newdata would not include the event times).

type

specify the type of prediction:

"surv"survival probabilities
"cumhaz"cumulative hazard
"hazard"hazard
"density"density
"hr"hazard ratio
"sdiff"survival difference
"hdiff"hazard difference
"loghazard"log hazards
"meansurv"mean survival
"meansurvdiff"mean survival difference
"odds"odds
"or"odds ratio
"margsurv"marginal (population) survival
"marghaz"marginal (population) hazard
"marghr"marginal (population) hazard ratio
"meanhaz"mean hazard
"af"attributable fraction
"fail"failure (=1-survival)
"margfail"marginal failure (=1-marginal survival)
"meanmargsurv"mean marginal survival, averaged over the frailty distribution
"uncured"distribution for the uncured

grid

whether to merge newdata with a regular sequence of event times (default=FALSE)

seqLength

length of the sequence used when grid=TRUE

se.fit

whether to calculate confidence intervals (default=FALSE)

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"))

exposed

a function that takes newdata and returns a transformed data-frame for those exposed or the counterfactual (defaults to incrementing ``var'')

var

specify the variable name or names for the exposed/unexposed (names are given as characters)

keep.attributes

Boolean to determine whether the output should include the newdata as an attribute (default=TRUE)

use.gr

Boolean to determine whether to use gradients in the variance calculations when they are available (default=TRUE)

…

additional arguments (for generic compatibility)

Value

A data-frame with components Estimate, lower and upper, with an attribute "newdata" for the newdata data-frame.

Methods

object= "stpm2": an stpm2 fit

Details