ggmcmc (version 1.5.1.1)

binary: Simulated data for a binary logistic regression and its MCMC samples

Description

Simulate a dataset with one explanatory variable and one binary outcome variable using (y ~ dbern(mu); logit(mu) = theta[1] + theta[2] * X). The data loads two objects: the observed y values and the coda object containing simulated values from the posterior distribution of the intercept and slope of a logistic regression. The purpose of the dataset is only to show the possibilities of the ggmcmc package.

Usage

data(binary)

Format

Two objects, namely:

s.binary

A coda object containing posterior distributions of the intercept (theta[1]) and slope (theta[2]) of a logistic regression with simulated data.

y.binary

A numeric vector containing the observed values of the outcome in the binary regression with simulated data.

Examples

# NOT RUN {
data(binary)
str(s.binary)
str(y.binary)
table(y.binary)
# }