PRNGNorNormal: Pseudo-Random Number Generation of Correlated Continuous...

In lalondetl/PRNG:

Description

This function produces pseudo-random numbers for responses for correlated (longitudinal) data. The responses are generated as continuous (Normal), using a normal random effect to induce autocorrelation. The predictors must be provided as a vector. The function returns a response vector, labeled "Outcomes".

Usage

PRNGNorNormal(M, mvec, mu_r, s_r, s, beta0, beta1, x, seed)

Arguments

M	The number of groups in the resulting data.
mvec	A vector indicating the length of each group in the data.
mu_r	The mean of the normal random effect.
s_r	The standard deviation of the normal random effect.
s	The standard deviation of the random error associated with the response.
beta0	The true intercept in the systematic component of the model.
beta1	The true slope in the systematic component of the model.
x	A vector of predictor values.
seed	The seed for data generation.

Examples

PRNGNorNormal()

lalondetl/PRNG documentation built on May 20, 2019, 3:06 p.m.