R/00_papua_new_guinea.R

################################################################################
#
#' Poverty Probability Index (PPI) lookup table for Papua New Guinea 2023
#'
#' @format A data frame with 9 columns and 101 rows:
#' \describe{
#' \item{\code{score}}{PPI score}
#' \item{\code{percentile20_wi}}{Below 20th percentile wealth index}
#' \item{\code{percentile40_wi}}{Below 40th percentile wealth index}
#' \item{\code{percentile60_wi}}{Below 60th percentile wealth index}
#' \item{\code{percentile80_wi}}{Below 80th percentile wealth index}
#' \item{\code{percentile20_wi_ur}}{Below 20th percentile wealth index urban/rural}
#' \item{\code{percentile40_wi_ur}}{Below 40th percentile wealth index urban/rural}
#' \item{\code{percentile60_wi_ur}}{Below 60th percentile wealth index urban/rural}
#' \item{\code{percentile80_wi_ur}}{Below 80th percentile wealth index urban/rural}
#' }
#'
#' @examples
#'   # Access Papua New Guinea PPI table
#'   ppiPNG2023
#'
#'   # Given a specific PPI score (from 0 - 100), get the row of poverty
#'   # probabilities from PPI table it corresponds to
#'   ppiScore <- 50
#'   ppiPNG2023[ppiPNG2023$score == ppiScore, ]
#'
#'   # Use subset() function to get the row of poverty probabilities corresponding
#'   # to specific PPI score
#'   ppiScore <- 50
#'   subset(ppiPNG2023, score == ppiScore)
#'
#'   # Given a specific PPI score (from 0 - 100), get a poverty probability
#'   # based on a specific poverty definition. In this example, the USAID
#'   # extreme poverty definition
#'   ppiScore <- 50
#'   ppiPNG2023[ppiPNG2023$score == ppiScore, "percentile20_wi"]
#'
#' @source \url{https://www.povertyindex.org}
#'
#
################################################################################
"ppiPNG2023"

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ppitables documentation built on May 29, 2024, 5:22 a.m.