R/immigration.R

In cregg: Simple Conjoint Tidying, Analysis, and Visualization

#' @rdname immigration
#' @docType data
#' @title Immigration Conjoint Experiment Dataset from Hainmueller et. al. (2014)
#' @description A dataset containing the results of a conjoint survey of a representative sample of American adults who were asked to choose which hypothetical immigrants they think should be admitted into the United States. Each row corresponds to a single profile presented to the respondent. The dataset results from a mostly full factorial design with restrictions on two combinations of features. (1) Profile immigrants from \samp{CountryOfOrigin} \dQuote{India}, \dQuote{Germany}, \dQuote{France}, \dQuote{Mexico}, \dQuote{Philippines}, and \dQuote{Poland} could be paired only with \samp{ReasonForApplication} \dQuote{Seek better job} or \dQuote{Reunite with family}; profiles from the remaining countries could be paired with any \samp{ReasonForApplication}. (2) Profile immigrants with \samp{Job} \dQuote{Financial Analyst}, \dQuote{Computer Programmer}, \dQuote{Research Scientist}, or \dQuote{Doctor} could not be paired with \samp{Education} levels \dQuote{No Formal}, \dQuote{4th Grade}, \dQuote{8th Grade}, or \dQuote{High School}. All other features were fully randomized against all other features.
#' @format A data frame (with additional \dQuote{cj_df} class) with 13960 observations on the following 16 variables.
#'  \describe{
#'    \item{\samp{CaseID}}{a numeric vector indicating the respondent to which the particular profile corresponds}
#'    \item{\samp{contest_no}}{a numeric vector indicating the number of the task to which the profile corresponds}
#'    \item{\samp{Education}}{a factor with levels \dQuote{No formal}, \dQuote{4th grade}, \dQuote{8th grade}, \dQuote{High school}, \dQuote{Two-year college}, \dQuote{college Degree}, \dQuote{Graduate degree}}
#'    \item{\samp{Gender}}{a factor with levels \dQuote{Female}, \dQuote{Male}}
#'    \item{\samp{CountryOfOrigin}}{a factor with levels \dQuote{India}, \dQuote{Germany}, \dQuote{France}, \dQuote{Mexico}, \dQuote{Philippines}, \dQuote{Poland}, \dQuote{China}, \dQuote{Sudan}, \dQuote{Somalia}, \dQuote{Iraq}}
#'    \item{\samp{ReasonForApplication}}{a factor with levels \dQuote{Reunite with family}, \dQuote{Seek better job}, \dQuote{Escape persecution}}
#'    \item{\samp{Job}}{a factor with levels \dQuote{Janitor}, \dQuote{Waiter}, \dQuote{Child care provider}, \dQuote{Gardener}, \dQuote{Financial analyst}, \dQuote{Construction worker}, \dQuote{Teacher}, \dQuote{Computer programmer}, \dQuote{Nurse}, \dQuote{Research scientist}, \dQuote{Doctor}}
#'    \item{\samp{JobExperience}}{a factor with levels \dQuote{None}, \dQuote{1-2 years}, \dQuote{3-5 years}, \dQuote{5+ years}}
#'    \item{\samp{JobPlans}}{a factor with levels \dQuote{Will look for work}, \dQuote{Contract with employer}, \dQuote{Interviews with employer}, \dQuote{No plans to look for work}}
#'    \item{\samp{PriorEntry}}{a factor with levels \dQuote{Never}, \dQuote{Once as tourist}, \dQuote{Many times as tourist}, \dQuote{Six months with family}, \dQuote{Once w/o authorization}}
#'    \item{\samp{LanguageSkills}}{a factor with levels \dQuote{Fluent English}, \dQuote{Broken English}, \dQuote{Tried English but unable}, \dQuote{Used interpreter}}
#'    \item{\samp{ChosenImmigrant}}{a numeric vector denoting whether the immigrant profile was selected}
#'    \item{\samp{ethnocentrism}}{a numeric vector}
#'    \item{\samp{profile}}{a numeric vector giving the profile number}
#'    \item{\samp{LangPos}}{a numeric vector}
#'    \item{\samp{PriorPos}}{a numeric vector}
#'  }
#' @source Hainmueller, J., Hopkins, D., and Yamamoto T. 2014. \dQuote{Causal Inference in Conjoint Analysis: Understanding Multi-Dimensional Choices via Stated Preference Experiments.} \emph{Political Analysis} 22(1): 1-30. \url{http://doi.org/10.1093/pan/mpt024}
#' @note This is a modified version of the \samp{hainmueller} dataset available from the \href{https://cran.r-project.org/package=cjoint}{cjoint} package.
#' @examples
#' \donttest{
#' data("immigration")
#' 
#' # view constraints between features
#' subset(cj_props(immigration, ~ Job + Education, id = ~ CaseID), Proportion == 0)
#' subset(cj_props(immigration, ~ ReasonForApplication + CountryOfOrigin, 
#'                 id = ~ CaseID), Proportion == 0)
#' 
#' # AMCEs with interactions for constraints
#' f1 <- ChosenImmigrant ~ Gender + Education * Job +
#'          LanguageSkills + CountryOfOrigin * ReasonForApplication + 
#'          JobExperience + JobPlans + PriorEntry
#' cj(immigration, f1, id = ~ CaseID)
#' }
#' @usage data(immigration)
#' @seealso \code{\link{cj}} \code{\link{taxes}} \code{\link{cj_df}}
"immigration"