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#' @templateVar MODEL_FUNCTION ra_noRA
#' @templateVar CONTRIBUTOR
#' @templateVar TASK_NAME Risk Aversion Task
#' @templateVar TASK_CODE ra
#' @templateVar TASK_CITE
#' @templateVar MODEL_NAME Prospect Theory, without risk aversion (RA) parameter
#' @templateVar MODEL_CODE noRA
#' @templateVar MODEL_CITE (Sokol-Hessner et al., 2009)
#' @templateVar MODEL_TYPE Hierarchical
#' @templateVar DATA_COLUMNS "subjID", "gain", "loss", "cert", "gamble"
#' @templateVar PARAMETERS \code{lambda} (loss aversion), \code{tau} (inverse temperature)
#' @templateVar REGRESSORS
#' @templateVar POSTPREDS "y_pred"
#' @templateVar LENGTH_DATA_COLUMNS 5
#' @templateVar DETAILS_DATA_1 \item{subjID}{A unique identifier for each subject in the data-set.}
#' @templateVar DETAILS_DATA_2 \item{gain}{Possible (50\%) gain outcome of a risky option (e.g. 9).}
#' @templateVar DETAILS_DATA_3 \item{loss}{Possible (50\%) loss outcome of a risky option (e.g. 5, or -5).}
#' @templateVar DETAILS_DATA_4 \item{cert}{Guaranteed amount of a safe option. "cert" is assumed to be zero or greater than zero.}
#' @templateVar DETAILS_DATA_5 \item{gamble}{If gamble was taken, gamble == 1; else gamble == 0.}
#' @templateVar LENGTH_ADDITIONAL_ARGS 0
#'
#' @template model-documentation
#'
#' @export
#' @include hBayesDM_model.R
#' @include preprocess_funcs.R
#' @references
#' Sokol-Hessner, P., Hsu, M., Curley, N. G., Delgado, M. R., Camerer, C. F., Phelps, E. A., & Smith, E. E. (2009). Thinking like a Trader Selectively Reduces Individuals' Loss Aversion. Proceedings of the National Academy of Sciences of the United States of America, 106(13), 5035-5040. https://www.pnas.org/content/106/13/5035
#'
ra_noRA <- hBayesDM_model(
task_name = "ra",
model_name = "noRA",
model_type = "",
data_columns = c("subjID", "gain", "loss", "cert", "gamble"),
parameters = list(
"lambda" = c(0, 1, 5),
"tau" = c(0, 1, 30)
),
regressors = NULL,
postpreds = c("y_pred"),
preprocess_func = ra_preprocess_func)
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