Description Usage Arguments Author(s) References Examples

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.

1 | ```
glmmSimData(seed=12345)
``` |

`seed` |
A positive integer which acts the seed for random data generation. |

Matt Wand[email protected] and James Yu[email protected]

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>.

1 2 3 4 5 6 | ```
# 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))
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.