R/mlbook_data.R

In psycCleaning: Data Cleaning for Psychological Analyses

#' mlbook_data 
#'
#' Classic data-set from Snijders, Tom A.B., and Bosker, Roel J. Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling, second edition.
#'
#' @format A data frame with 3758 rows and 34 variables:
#' \describe{
#'   \item{schoolnr}{School ID}
#'   \item{pupilNR_new}{Student Identifier (Level 1 units)}
#'   \item{langPOST}{Student language score}
#'   \item{ses}{Student socioeconomic score, grand-mean centered (in points, M = 0))}
#'   \item{IQ_verb}{Student verbal IQ, grand-mean centered (in points, M = 0)}
#'   \item{sex}{Student binary gender, 1 = female, 0 = not female}
#'   \item{Minority}{Student minority status, 1 = minoritized, 0 = not minoritized}
#'   \item{denomina}{School-level religious denominations, 5 categories}
#'   \item{female_dum}{Dummy coded sex}
#'   \item{female_eff}{Effect-coded sex}
#'   \item{female_CMC}{Group-mean-centered of female_eff}
#'   \item{fempct_agg}{Aggregated mean female_dum for each school}
#'   \item{Zfempct_agg}{Z-scored aggregated mean female_dum for each school}
#'   \item{ses_CMC}{Group-mean-centered SES}
#'   \item{Zses_CMC}{Z-scored group-mean-centered SES}
#'   \item{ses_agg}{Aggregated mean SES for each school}
#'   \item{Zses_agg}{Z-scored aggregated mean SES for each school}
#' }
#' @source \url{https://www.stats.ox.ac.uk/~snijders/mlbook.htm}
"mlbook_data"