zibHelpers

Helper functions for handling results from Bayesian Zero-Inflated Beta Regressions in R

Christopher Gandrud

Description

Contains a number of functions to help diagnose and examine results from Bayesian zero-inflated beta regressions estimated with the zoib package.

For more information about Bayesian zero-inflated regression see pages 12-14 of Liu and Kong. This piece has a good summary of zero/one inflated beta regression generally.

Functions

• GelmanDiag: extract Gelman-Rubin convergence diagnostics

• SummaryZib: extract and summarise posterior distribution

• zibPlot: plot parameter posteriors from Zero-inflated Beta Regressions

Example

# Load packages
library(zoib)
library(zibHelpers)

# Run example of clustered zero-inflated beta regression from
# Liu and Kong (under review, 12-14)

# Load data
data("AlcoholUse", package = "zoib")
AlcoholUse$Grade <- as.factor(AlcoholUse$Grade)

nIter = 50 # Number of iterations, including burn-in

# Estimate
Out <- zoib(Percentage ~ Grade + Days + Gender|1|Grade + Days + Gender|1,
            data = AlcoholUse, random = 1, EUID = AlcoholUse$County,
            zero.inflation = TRUE, one.inflation = FALSE, joint = FALSE,
            n.iter = nIter)

# Gelman-Rubin diagnostics
GelmanDiag(Out, nIter)

# Summarise the posterior
SummaryZib(Out, nIter)

# Plot the posterior summary
zibPlot(Out, iter = nIter)

zibPlot in this example creates the following plot. Note that coefficients are show in the order in which they are entered into the model. b*[1] refers to the intercepts. Those prefixed with b are for the beta continuous part. Those with b0 are for the discrete part where the outcome is the probability that the dependent variable = 0.

You can add custom variable labels with the xlab argument.

Install

devtools::install_github('christophergandrud/zibHelpers')

---

Licensed under MIT