cregg: Simple Conjoint Tidying, Analysis, and Visualization

#' @rdname taxes
#' @docType data
#' @title Tax Preference Conjoint Experiment Dataset from Ballard-Rosa et al. (2016)
#' @description A dataset containing the results of a fully randomized conjoint survey of a representative sample of 2000 American adults who were asked to choose between alternative tax rate policies. Variables \samp{taxrate1}-\samp{taxrate6} refer to tax rates for different income brackets and \samp{taxrev} refers to levels of total tax revenue.
#' @format A data frame (with additional \dQuote{cj_df} class) with 32000 observations on the following 13 variables. Each row corresponds to a single profile presented to a respondent.
#'  \describe{
#'    \item{\samp{chose_plan}}{A numeric vector denoting whether the immigrant profile was selected (=1) or not (=0).}
#'    \item{\samp{taxrate1}}{An experimental factor with levels \dQuote{<10k: 0\%}, \dQuote{<10k: 5\%}, \dQuote{<10k: 15\%}, \dQuote{<10k: 25\%}.}
#'    \item{\samp{taxrate2}}{An experimental factor with levels \dQuote{10-35k: 5\%}, \dQuote{10-35k: 15\%}, \dQuote{10-35k: 25\%}, \dQuote{10-35k: 35\%}.}
#'    \item{\samp{taxrate3}}{An experimental factor with levels \dQuote{35-85k: 5\%}, \dQuote{35-85k: 15\%}, \dQuote{35-85k: 25\%}, \dQuote{35-85k: 35\%}.}
#'    \item{\samp{taxrate4}}{An experimental factor with levels \dQuote{85-175k: 5\%}, \dQuote{85-175k: 15\%}, \dQuote{85-175k: 25\%}, \dQuote{85-175k: 35\%}.}
#'    \item{\samp{taxrate5}}{An experimental factor with levels \dQuote{175-375k: 5\%}, \dQuote{175-375k: 15\%}, \dQuote{175-375k: 25\%}, \dQuote{175-375k: 35\%}, \dQuote{175-375k: 45\%}.}
#'    \item{\samp{taxrate6}}{An experimental factor with levels \dQuote{>375k: 5\%}, \dQuote{>375k: 15\%}, \dQuote{>375k: 25\%}, \dQuote{>375k: 35\%}, \dQuote{>375k: 45\%}, \dQuote{>375k: 55\%}.}
#'    \item{\samp{taxrev}}{An experimental factor with levels \dQuote{<75\%}, \dQuote{75-95\%}, \dQuote{95-105\%}, \dQuote{105-125\%}, \dQuote{>125\%}.}
#'    \item{\samp{inequality_aversion}}{A covariate specifying whether respondent is inequality averse (=1) or not (=0).}
#'    \item{\samp{taxes_harm_economy}}{A covariate specifying whether respondent believes taxes harm the economy (=1) or not (=0).}
#'    \item{\samp{partyid}}{A factor specifying the respondent's party identification; one of \dQuote{Independent}, \dQuote{Democrat}, \dQuote{Republican}.}
#'    \item{\samp{ID}}{A numeric vector indicating the respondent to which the profile corresponds.}
#'    \item{\samp{weight}}{A numeric vector containing survey weights.}
#'  }
#' @source Ballard-Rosa, Cameron, Lucy Martin, and Kenneth Scheve. 2016. \dQuote{The Structure of American Income Tax Policy Preferences.} \emph{The Journal of Politics} 79(1): 1-16. \url{http://doi.org/10.1086/687324}
#' @examples
#' \donttest{
#' data("taxes")
#' f1 <- chose_plan ~ taxrate1 + taxrate2 + taxrate3 + 
#'         taxrate4 + taxrate5 + taxrate6 + taxrev
#' cj(taxes, f1, id = ~ ID, weights = ~     weight)
#' }
#' @usage data(taxes)
#' @seealso \code{\link{cj}} \code{\link{immigration}} \code{\link{cj_df}}
"taxes"