R/majete_data.r

In geosample: Construction of Geostatistical Sampling Designs

##' @title Majete malaria prevalence data
##' @description This data-set relates to malaria prevalence study conduted in Majete (Chikwawa), southern Malawi.
##' The variables are as follows:
##'
##' \itemize{
##'   \item \code{rdt:} Rapid diagnostic test result;  0 = negative, 1 = positive.
##'   \item \code{age:} Age of the individual in months.
##'   \item \code{quintile:} Wealth quintile; ranging from 1 = poor to 5 = well to do.
##'   \item \code{itn:} Insecticide treated bed-net usage; 0 = no, 1 = yes.
##'   \item \code{elev:} Elevation; height above sea level in meters.
##'   \item \code{ndvi:} Normalised difference vegetation index (greenness).
##'   \item \code{agecat:} Age category; 1 = child, 2 = adult.
##'   \item \code{geometry:} Point or household locations (UTM).
##' }
##'
##' @docType data
##' @keywords datasets
##' @name majete
##' @usage data("majete")
##' @format A data frame with 747 features and 7 variables
##' @references Kabaghe A N, Chipeta M G, McCann R S, Phiri K S, Van Vugt M, Takken W, Diggle P J, and Terlouw D J. (2017). Adaptive geostatistical sampling enables efficient identification of malaria hotspots in repeated cross-sectional surveys in rural Malawi, \emph{PLoS One} \bold{12}(2) pp. e0172266
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