% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/abortionopposition.R
\docType{data}
\name{AbortionOpposition}
\alias{AbortionOpposition}
\title{Public Opinion on Abortion Across U.S. States}
\format{
A data frame with 51 observations and 9 variables:
\describe{
  \item{state}{Factor. U.S. state or the District of Columbia.}
  \item{abortion_opposition}{Numeric. Proportion of adults who believe
        abortion should be illegal in all or most cases, bounded in the
        (0,1) interval, based on the Pew Research Center 2023--24
        Religious Landscape Study. This is the response variable used
        in the regression analyses.}
  \item{religious_attendance}{Numeric. Percentage of adults who report
        attending religious services at least once a week, based on the
        Pew Research Center 2023--24 Religious Landscape Study.}
  \item{income}{Numeric. Mean household income (in U.S. dollars) in 2024.}
  \item{sex_ratio}{Numeric. Number of males per 100 females in 2024.}
  \item{female}{Numeric. Proportion of the population that is female,
        bounded in the (0,1) interval, in 2024.}
  \item{pop_18_24}{Numeric. Percentage of the population aged 18--24 years,
        obtained directly from the 2024 American Community Survey (ACS)
        1-Year Estimates (Table S0101).}
  \item{bachelors}{Numeric. Percentage of adults aged 25 and older with a
        bachelor's degree or higher, in 2024.}
  \item{urban}{Numeric. Percentage of the population living in urban areas,
        based on 2020 U.S. Census Bureau estimates.}
}
}
\source{
Pew Research Center. 2023--24 Religious Landscape Study.

Pew Research Center (2025). Americans' Views on Abortion Differ by State.

World Population Review (2024). Per Capita Income by State
(Mean Household Income 2024 column).

World Population Review (2024). Male to Female Ratio by State.

World Population Review (2024). Educational Attainment by State
(Bachelors or Higher 2024 column).

World Population Review (2020 U.S. Census data). Most Urban States
(Urban Population Pct 2020 column).

U.S. Census Bureau. American Community Survey (ACS) 1-Year Estimates (2024),
Table S0101: Age and Sex.
}
\usage{
data(AbortionOpposition)
}
\description{
This dataset examines the relationship between public opposition to abortion
and demographic, religious, and socioeconomic characteristics across the
50 U.S. states and the District of Columbia. The response variable is a
proportion bounded in the (0,1) interval, making the data suitable for
simplex regression and beta regression analyses.
}
\details{
The dataset was assembled by the package authors from multiple publicly
available sources. The response variable, \code{abortion_opposition},
was obtained from the Pew Research Center 2023--24 Religious Landscape
Study and rescaled to the (0,1) interval.

The explanatory variables were obtained as follows:
\enumerate{
  \item \code{religious_attendance} was obtained from the Pew Research Center
        2023--24 Religious Landscape Study.
  \item \code{income} and \code{sex_ratio} were obtained from
        World Population Review using U.S. Census Bureau estimates.
  \item \code{female} was derived from \code{sex_ratio} and is provided
        on the (0,1) proportion scale, unlike the other percentage-based
        explanatory variables in this dataset, which are on the 0--100
        scale. Note that \code{sex_ratio} and \code{female} are
        mathematically related (\code{female = 100 / (100 + sex_ratio)})
        and should generally not be included together as covariates in
        the same regression model, as doing so would introduce
        near-perfect collinearity.
  \item \code{pop_18_24} corresponds to the percent estimate of the
        population aged 18--24 years reported directly in Table S0101
        (Age and Sex) of the 2024 American Community Survey (ACS)
        1-Year Estimates.
  \item \code{bachelors} was obtained from World Population Review
        using U.S. Census Bureau estimates for 2024.
  \item \code{urban} was obtained from World Population Review and is
        based on 2020 U.S. Census Bureau data, the most recent Census
        estimate of urbanization by state available at the time this
        dataset was compiled. All other explanatory variables in this
        dataset reflect 2023--24 estimates.
}
}
\examples{
# Load the data
data(AbortionOpposition)

# Quick overview
head(AbortionOpposition)
str(AbortionOpposition)

# Summary statistics
summary(AbortionOpposition)

# Relationship between religious attendance and abortion opposition
plot(abortion_opposition ~ religious_attendance,
     data = AbortionOpposition,
     pch = 19,
     xlab = "Religious attendance (\%)",
     ylab = "Abortion opposition (proportion)")

# Correlation among numeric variables
cor(AbortionOpposition[, c("abortion_opposition",
                        "religious_attendance",
                        "income",
                        "sex_ratio",
                        "female",
                        "pop_18_24",
                        "bachelors",
                        "urban")])
}
\keyword{datasets}
