PRNGBinBeta: Pseudo-Random Number Generation of Correlated Binary...
In lalondetl/PRNG:

Description Usage Arguments Examples

View source: R/PRNGBinBeta.R

This function produces pseudo-random numbers for responses for correlated (longitudinal) data. The responses are generated as either binary (Bernoulli) data or count (Binomial), using a transformed Beta random effect to induce autocorrelation. Once the Beta-distributed random effects are generated, the values are transformed according to a logit transformation to ensure they interact with the response similarly to otherpredictors. The predictors must be provided as a vector. The function returns a response vector, labeled "Outcomes".

1	PRNGBinBeta(M, mvec, D, beta0, beta1, x, seed)

`M`	The number of groups in the resulting data.
`mvec`	A vector indicating the length of each group in the data.
`D`	A vector of denominators for each response; a vector of 1's indicates Bernoulli data.
`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.