Simulated data for a binary logistic regression and its MCMC samples
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.
data(binary)
Two objects, namely:
A coda object containing posterior distributions of the intercept (theta[1]) and slope (theta[2]) of a logistic regression with simulated data.
A numeric vector containing the observed values of the outcome in the binary regression with simulated data.
Simulated data for ggmcmc
data(binary) str(s.binary) str(y.binary) table(y.binary)
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