R: Retrospective risk reclassification table

reclass {pec} | R Documentation

## Retrospective risk reclassification table

### Description

Retrospective table of risks predicted by two different methods, models, algorithms

### Usage

    reclass(
      object,
      reference,
      formula,
      data,
      time,
      cause,
      cuts = seq(0, 100, 25),
      digits = 2
    )

### Arguments

`object` | Either a list with two elements. Each element should either be a vector with probabilities, or an object for which `predictSurvProb` or `predictEventProb` can extract predicted risk based on data.
`reference` | Reference prediction model.
`formula` | A survival formula as obtained either with `prodlim::Hist` or `survival::Surv` which defines the response in the `data`.
`data` | Used to extract the response from the data and passed on to `predictEventProb` to extract predicted event probabilities.
`time` | Time interest for prediction.
`cause` | For competing risk models the cause of interest. Defaults to all available causes.
`cuts` | Risk quantiles to group risks.
`digits` | Number of digits to show for the predicted risks

### Details

All risks are multiplied by 100 before

### Value

reclassification tables: overall table and one conditional table for each cause and for subjects event free at time interest.

### Author(s)

Thomas A. Gerds <tag@biostat.ku.dk>

### See Also

predictStatusProb

### Examples

    ## Not run:
    library(survival)
    set.seed(40)
    d <- prodlim::SimSurv(400)
    nd <- prodlim::SimSurv(400)
    Models <- list("Cox.X2"=coxph(Surv(time,status)~X2,data=d,x=TRUE,y=TRUE),
                   "Cox.X1.X2"=coxph(Surv(time,status)~X1+X2,data=d,x=TRUE,y=TRUE))
    rc <- reclass(Models,formula=Surv(time,status)~1,data=nd,time=5)
    print(rc)
    plot(rc)

    set.seed(40)
    library(riskRegression)
    library(prodlim)
    dcr <- prodlim::SimCompRisk(400)
    ndcr <- prodlim::SimCompRisk(400)
    crPred5 <- list("X2"=predictEventProb(CSC(Hist(time,event)~X2,data=dcr),newdata=ndcr,times=5),
                    "X1+X2"=predictEventProb(CSC(Hist(time,event)~X1+X2,data=dcr),newdata=ndcr,times=5))
    rc <- reclass(crPred5,Hist(time,event)~1,data=ndcr,time=3)
    print(rc)

    reclass(crPred5,Hist(time,event)~1,data=ndcr,time=5,cuts=100*c(0,0.05,0.1,0.2,1))

    ## End(Not run)

[Package pec version 2022.03.06 Index]