dgp_dicp {tramicp}

Simple data-generating process for illustrating tramicp

Description

Simple data-generating process for illustrating tramicp

Usage

dgp_dicp(
  n = 1000,
  K = 6,
  nenv = 2,
  bx3 = stats::rnorm(1),
  ge = stats::rnorm(nenv),
  ae = stats::rnorm(nenv),
  mod = "polr",
  interacting = FALSE,
  rm_censoring = TRUE,
  cfb = c(-3, 1.35),
  cfx = stats::rnorm(2),
  bx2x1 = stats::rnorm(1)
)

Arguments

n

Sample size

K

Number of outcome classes or order of Bernstein polynomial

nenv

Number of environments

bx3

Effect of Y on X3

ge

Environment specific effect

ae

Environment specific effect

mod

Type of model

interacting

Toggle baseline interaction with env

rm_censoring

Remove censoring from simulated responses

cfb

Baseline coefs

cfx

Shift coefs

bx2x1

coef from x2 to x1

Details

Simulates from X2 -> X1 -> Y -> X3, with E affecting X1, X2, X3, but not Y.

Value

data.frame with simulated data