R/arnold2013.R

In TreeBUGS: Hierarchical Multinomial Processing Tree Modeling

#' Data of a Source-Monitoring Experiment
#'
#' Dataset of a source-monitoring experiment by Arnold, Bayen, Kuhlmann, and
#' Vaterrodt (2013) using a 2 (Source; within) x 3 (Expectancy; within) x 2
#' (Time of Schema Activation; between) mixed factorial design.
#'
#' @details Eighty-four participants had to learn statements that were either
#' presented by a doctor or a lawyer (Source) and were either typical for
#' doctors, typical for lawyers, or neutral (Expectancy). These two types of
#' statements were completely crossed in a balanced way, resulting in a true
#' contingency of zero between Source and Expectancy. Whereas the profession
#' schemata were activated at the time of encoding for half of the participants
#' (encoding condition), the other half were told about the profession of the
#' sources just before the test (retrieval condition). After the test,
#' participants were asked to judge the contingency between item type and source
#' (perceived contingency pc).
#'
#' @format A data frame 13 variables:
#' \describe{
#'   \item{\code{subject}}{Participant code}
#'   \item{\code{age}}{Age in years}
#'   \item{\code{group}}{ Between-subject factor "Time of Schema Activation":
#'                         Retrieval vs. encoding condition}
#'   \item{\code{pc}}{perceived contingency}
#'   \item{\code{EE}}{Frequency of "Source E" responses to items from source "E"}
#'   \item{\code{EU}}{Frequency of "Source U" responses to items from source "E"}
#'   \item{\code{EN}}{Frequency of "New" responses to items from source "E"}
#'   \item{\code{UE}}{Frequency of "Source E" responses to items from source "E"}
#'   \item{\code{UU}}{Frequency of "Source U" responses to items from source "E"}
#'   \item{\code{UN}}{Frequency of "New" responses to items from source "E"}
#'   \item{\code{NE}}{Frequency of "Source E" responses to new items}
#'   \item{\code{NU}}{Frequency of "Source U" responses to new items}
#'   \item{\code{NN}}{Frequency of "New" responses to new items}
#' }
#' @references Arnold, N. R., Bayen, U. J., Kuhlmann, B. G., & Vaterrodt, B.
#'   (2013). Hierarchical modeling of contingency-based source monitoring: A
#'   test of the probability-matching account. Psychonomic Bulletin & Review,
#'   20, 326-333.
#'
#' @examples
#' head(arnold2013)
#'
#' \dontrun{
#' # fit hierarchical MPT model for encoding condition:
#' EQNfile <- system.file("MPTmodels/2htsm.eqn", package = "TreeBUGS")
#' d.encoding <- subset(arnold2013, group == "encoding", select = -(1:4))
#' fit <- betaMPTcpp(EQNfile, d.encoding,
#'   n.thin = 5,
#'   restrictions = list("D1=D2=D3", "d1=d2", "a=g")
#' )
#' # convergence
#' plot(fit, parameter = "mean", type = "default")
#' summary(fit)
#' }
"arnold2013"