R/DatMA.R

In Frames2: Estimation in Dual Frame Surveys

#' @name DatMA
#' @aliases DatMA
#' @docType data
#' @title Database of students' program choice for frame A
#' 
#' @description This dataset contains some variables regarding the program choice for a sample of 180 students included in the sampling frame A.
#' @usage DatMA
#' @details The sample, of size \eqn{n_A = 180}, has been drawn from a population of \eqn{N_A = 5500} students according to a proportional-to-size sampling desing according to the size of the school. So, students
#'  attending bigger schools have a higher probability of being selected in the sample. \eqn{N_{ab} = 2000} of the students composing the population belongs also to frame B.
#' @format
#' \describe{
#'    \item{Id_Pop}{An integer from 1 to \eqn{N}, with \eqn{N} the number of students in the whole population, identifying the student within the population.}
#'    \item{Id_Frame}{An integer from 1 to \eqn{N_A}, with \eqn{N_A} the number of students in the frame, identifying the student within the frame.}
#'    \item{Prog}{A factor with three categories (academic, general and vocation) indicating the program choice of the student.}
#'    \item{Ses}{An ordinal factor with three categories (low, middle and high) indicating the socio-economical status of the student.}
#'    \item{Read}{A number indicating the mark of the student in a reading test.}
#'    \item{Write}{A number indicating the mark of the student in a writing test.}
#'    \item{Sch_Size}{A number indicating the size of the school the students belongs to.}
#'    \item{Domain}{A string indicating the domain each student belongs to. Possible values are "a" if student belongs to domain a or "ab" if student belongs to overlap domain.}
#'    \item{ProbA}{First order inclusion probability in frame A.}
#'    \item{ProbB}{First order inclusion probability in frame B. This probability is 0 for students included in domain a.}
#' }
#' @seealso \code{\link{DatPopM}}
#' @examples
#' data(DatMA)
#' attach(DatMA)
#' #Let perform a brief descriptive analysis for the main variable
#' summary (Prog)
#' #And let do the same for the numerical auxiliary variables Read and Write
#' summary(Read)
#' summary(Write)
#' @keywords datasets
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