getTrueModel {simulatorZ}R Documentation

getTrueModel

Description

The parametric bootstrap simulation depends on the true model of original sets. This function is to generate useful values from the true models for further analysis. We fit CoxBoost to the original sets and use the coefficients to simulate the survival and censoring time. grid, survH, censH, which are useful for this purpose. grid=grid corresponding to hazard estimations censH and survH survH=cumulative hazard for survival times distribution censH=cumulative hazard for censoring times distribution

Usage

getTrueModel(esets, y.vars, parstep, balance.variables = NULL)

Arguments

esets

a list of ExpressionSets, matrix or SummarizedExperiment

y.vars

a list of response variables

parstep

CoxBoost parameter

balance.variables

variable names to be balanced.

Value

returns a list of values: beta: True coefficients obtained by fitting CoxBoost to the original ExpressionSets grid: timeline grid corresponding to hazard estimations censH and survH survH: cumulative hazard for survival times distribution censH: cumulative hazard for censoring times distribution lp: true linear predictors

Author(s)

Yuqing Zhang, Christoph Bernau, Levi Waldron

Examples

library(curatedOvarianData)
data(GSE14764_eset)
data(E.MTAB.386_eset)
esets.list <- list(GSE14764=GSE14764_eset[1:500, 1:20], 
                   E.MTAB.386=E.MTAB.386_eset[1:500, 1:20])
rm(E.MTAB.386_eset, GSE14764_eset)

## simulate on multiple ExpressionSets
set.seed(8) 

y.list <- lapply(esets.list, function(eset){
  time <- eset$days_to_death
  cens.chr <- eset$vital_status
  cens <- rep(0, length(cens.chr))
  cens[cens.chr=="living"] <- 1
  return(Surv(time, cens))
})
   
res1 <- getTrueModel(esets.list, y.list, 100)
## Get true model from one set
res2 <- getTrueModel(esets.list[1], y.list[1], 100)
names(res2)
res2$lp
## note that y.list[1] cannot be replaced by y.list[[1]]

[Package simulatorZ version 1.16.0 Index]