MAZE (version 0.0.2)

DataGen: DataGen

Description

Generate data under zero-inflated mediation models and calculate the true effects

Usage

DataGen(distM, theta, K, num_Z = 0, n, B, x1, x2, zval = NULL, mval = 0)

Value

true_eff: a vector containing true effects (NIE1, NIE2, NIE, NDE, and CDE)

dat: a data frame containing variables:

• X: independent variable,

• Mobs: observed mediator values (with possibly false zeros)

• M: true mediator values,

• Y: outcome,

• Z: confounder variables (if any)

Arguments

distM

distribution of the mediator. One of 'zilonm', 'zinbm', and 'zipm' for zero-inflated log-normal, negative binomial, and Poisson mediators respectively

theta

vector of true parameter values

K

true number of component \(K\) in the zero-inflated mixture mediators. Default is \(K=1\) for zero-inflated (non-mixture) mediators

num_Z

number of confounder variables

n

number of observations to generate

B

the upper bound value \(B\) to be used in the probability mechanism of observing false zeros

x1

the first value of independent variable of interest

x2

the second value of independent variable of interest

zval

the value of confounders to be conditional on when calculating true effects

mval

the fixed value of mediator to be conditional on when calculating true CDE

Author

Meilin Jiang and Zhigang Li

Examples

betas.tr <- c(2, 0.12, -6.6, 6.3, -3.8, 0)
delta.tr <- 1.1
alpha0_k.tr <- c(0.4, 1.1)
alpha1_k.tr <- c(0.1, 0.5)
alphas.tr <- rbind(alpha0_k.tr,alpha1_k.tr)
xi0.tr <- -1.5
psi_km1.tr <- c(0.6)
gammas.tr <- c(-1.8, 0.5)
eta.tr <- 1
theta <- c(betas.tr, delta.tr, alphas.tr,
           xi0.tr, psi_km1.tr, gammas.tr, eta.tr)
out <- DataGen(distM = 'zilonm', theta, K = 2, num_Z=0,
               n = 200, B = 20, x1 = 0, x2 = 1, zval = NULL, mval = 0)
(true_eff <- out$true_eff)
dat <- out$dat