glmmSimData function

Simulation of data from a generalized linear mixed model.

Section 4.1.2 of the refence below descries a simulation study with data generated from a probit mixed model with six fixed effects parameters and a bivariate random effects vector having a 2 by 2 symmetric positive definite covariance matrix. The function simulates a data set from this model with 2500 groups and the number of observation in each group being a random draw from 20,21,...,30.

glmmSimData(seed=12345)

Arguments

• seed: A positive integer which acts the seed for random data generation.

Author(s)

Matt Wandmatt.wand@uts.edu.au and James Yujames.yu@student.uts.edu.au

References

Hall, P.,Johnstone, I.M., Ormerod, J.T., Wand, M.P. and Yu, J. (2018). Fast and accurate binary response mixed model analysis via expectation propagation. arXiv:1805.08423v1.

Examples

# Obtain simulated data corresponding to the simulation study in Section 4.1.2. of 
# Hall et al. (2018):

library(glmmEP)
dataObj <- glmmSimData(seed=54321)
print(names(dataObj))