simNonNestedNormal: simulations with two gaussian distributed predictors

In thomashielscher/nonnestcox: Comparing nonnested CoxPH models

Description

simulations with two gaussian distributed predictors

Usage

simNonNestedNormal(B, n, beta1, beta2, censrate = 0)

Arguments

B	simulations runs
n	sample size
beta1	first coefficient
beta2	second coefficient
censrate	censoring rate for exponential model

Value

list

Examples

## Not run: 
require("survival")
require("lava")
# setup
simmat  <- expand.grid(n=c(100, 200, 350), beta1=c(0,0.5,1),beta2=c(0,1))
# simulations w/o censoring
simres <- t(apply(simmat, 1, function(d) unlist(simNonNestedNormal(B=10, n=d[1], beta1=d[2], beta2=d[3], censrate=0))))
simres <- cbind(simmat,simres)

## End(Not run)

thomashielscher/nonnestcox documentation built on Dec. 14, 2020, 5:16 a.m.