% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/AlcoholUse.R
\docType{data}
\name{AlcoholUse}
\alias{AlcoholUse}
\title{California Alcohol Use Data}
\format{
A data frame with multiple rows and variables:
\describe{
\item{Percentage}{numeric: percentage of students who drank alcohol}
\item{Grade}{factor: student grade level}
\item{Gender}{factor: student gender}
\item{MedDays}{numeric: mid-point of days bucket}
\item{Days}{numeric: days bucket}
\item{County}{factor: county identifier}
}

A data frame with 44 rows and 4 variables:
\describe{
\item{accuracy}{numeric: proportion of correct responses in a reading task}
\item{accuracy1}{numeric: transformed accuracy measure}
\item{dyslexia}{factor: dyslexia status (levels: "yes", "no")}
\item{iq}{numeric: IQ score}
}
}
\source{
\url{http://www.kidsdata.org}
Reading Skills Data

A dataset from Smithson and Verkuilen (2006) on reading accuracy, dyslexia status, and IQ scores.
The response variable \code{accuracy} is a proportion (0 < accuracy < 1), suitable for beta regression.

Smithson, M. & Verkuilen, J. (2006). \emph{A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables}.
\url{https://psycnet.apa.org/doi/10.1037/1082-989X.11.1.54}
}
\usage{
AlcoholUse
}
\description{
A county-level monthly alcohol use dataset from California students (grades 7-11, 2008-2010).
The response variable \code{Percentage} is a proportion (0 < Percentage < 1), suitable for zero-inflated beta regression.
}
\examples{
data(AlcoholUse)
str(AlcoholUse)
}
\keyword{datasets}
