Updating Namespace

Author: ManuelRausch

DESCRIPTION

@@ -11,7 +11,7 @@ Authors@R: c(
     person("Sebastian", "Hellmann", email = "[email protected]", 
     role = c("aut"), comment = c(ORCID = "0000-0002-3621-6343"))
        )
-Maintainer: Manuel Rausch <manuel.rausch@hochschule-rhein-waal.de>
+Maintainer: Manuel Rausch <manuel.rausch@ku.de>
 Description: Provides fitting functions and other tools for decision confidence 
     and metacognition researchers, including meta-d'/d', often considered to be 
     the gold standard to measure metacognitive efficiency, and information-theoretic measures of metacognition. 

NAMESPACE

@@ -4,6 +4,7 @@ export(estimateMetaI)
 export(fitConf)
 export(fitConfModels)
 export(fitMetaDprime)
+export(groupBMS)
 export(plotConfModelFit)
 export(simConf)
 import(ggplot2)
@@ -19,5 +20,6 @@ importFrom(stats,optim)
 importFrom(stats,plnorm)
 importFrom(stats,pnorm)
 importFrom(stats,qnorm)
+importFrom(stats,rgamma)
 importFrom(stats,rmultinom)
 importFrom(utils,tail)

R/fitConf.R

@@ -186,6 +186,7 @@
 #' @references Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. doi: 10.1214/aos/1176344136\cr
 #' @references Shekhar, M., & Rahnev, D. (2021). The Nature of Metacognitive Inefficiency in Perceptual Decision Making. Psychological Review, 128(1), 45–70. doi: 10.1037/rev0000249\cr
 #' @references Shekhar, M., & Rahnev, D. (2023). How Do Humans Give Confidence? A Comprehensive Comparison of Process Models of Perceptual Metacognition. Journal of Experimental Psychology: General. doi:10.1037/xge0001524\cr
+#' @references Peters, M. A. K., Thesen, T., Ko, Y. D., Maniscalco, B., Carlson, C., Davidson, M., Doyle, W., Kuzniecky, R., Devinsky, O., Halgren, E., & Lau, H. (2017). Perceptual confidence neglects decision-incongruent evidence in the brain. Nature Human Behaviour, 1(0139), 1–21. doi:10.1038/s41562-017-0139
 
 #' @examples
 #' # 1. Select one subject from the masked orientation discrimination experiment

R/fitConfModels.R

@@ -193,6 +193,21 @@
 #' The parameter \eqn{w} represents the weight that is put on the choice-irrelevant
 #' features in the confidence judgment. \eqn{w} and \eqn{\sigma} are fitted in
 #' addition to the set of shared parameters.
+#'
+#' ### \strong{Response-congruent evidence model (RCE)}
+#' The response-congruent evidence model represents the idea that observers use
+#' all available sensory information to make the discrimination decision, but for confidence judgements,
+#' they only consider evidence consistent with the selected decision and ignore evidence against the decision (Peters et al., 2017).
+#' The model assumes two separate samples of sensory evidence collected in each trial,
+#' each belonging to one possible identity of the stimulus.
+#' Both samples of sensory evidence \eqn{x_{-1}} and
+#' \eqn{x_1} are sampled from Gaussian distributions with a standard deviations of \eqn{\sqrt{1/2}}.
+#' The mean of \eqn{x_{-1}} is given by \eqn{(1 − S) \times 0.25 \times d}; the mean
+#' of \eqn{x_1} is given by \eqn{(1 + S) \times 0.25 \times d}. The sensory evidence
+#' used for the discrimination choice is \eqn{x = x_2 - x_1},
+#' which implies that the discrimination decision is equivalent to standard SDT.
+#' The confidence decision variable y is \eqn{y = - x_1} if the response R is -1 and \eqn{y = x_2} otherwise.
+
 
 #' @author
 #' Sebastian Hellmann, \email{[email protected]}\cr
@@ -212,6 +227,8 @@
 #' @references Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. doi: 10.1214/aos/1176344136\cr
 #' @references Shekhar, M., & Rahnev, D. (2021). The Nature of Metacognitive Inefficiency in Perceptual Decision Making. Psychological Review, 128(1), 45–70. doi: 10.1037/rev0000249\cr
 #' @references Shekhar, M., & Rahnev, D. (2023). How Do Humans Give Confidence? A Comprehensive Comparison of Process Models of Perceptual Metacognition. Journal of Experimental Psychology: General. doi:10.1037/xge0001524\cr
+#' @references Peters, M. A. K., Thesen, T., Ko, Y. D., Maniscalco, B., Carlson, C., Davidson, M., Doyle, W., Kuzniecky, R., Devinsky, O., Halgren, E., & Lau, H. (2017). Perceptual confidence neglects decision-incongruent evidence in the brain. Nature Human Behaviour, 1(0139), 1–21. doi:10.1038/s41562-017-0139
+
 
 #' @examples
 #' # 1. Select two subjects from the masked orientation discrimination experiment

R/groupBMS.R

@@ -80,6 +80,8 @@
 #' # Conduct group-level Bayesian model selection based on BIC
 #' ModelComp <- groupBMS(fitted_par, measure="BIC")
 #' ModelComp
+#'
+#' @importFrom stats rgamma
 #' @export
 groupBMS <- function(fits, measure = "BIC", opts=list()) {
   if (!measure %in% c("BIC", "AIC", "AICc"))
@@ -114,7 +116,7 @@ groupBMS <- function(fits, measure = "BIC", opts=list()) {
     res <- sum(g*(x - log(g+opts$eps) - log(K)))
     return(res)
   }
-  
+
   FreeEnergyNull <- sum(apply(mlp, 2, modelprobs_Null))
 
   # derive probabilities and free energy of the 'fixed-effect' analysis

R/int_fitCEV.R

@@ -1,5 +1,6 @@
 ###   Functions to fit the WEV model
 ### Model version described by (Rausch et al., 2023)
+
 fitCEV <-
   function(N_SA_RA, N_SA_RB, N_SB_RA, N_SB_RB,
            nInits, nRestart, nRatings, nCond, nTrials){

R/int_fitRCE.R

@@ -47,7 +47,7 @@ fitRCE <-
 
 
     logL <- apply(inits, MARGIN = 1,
-                  function(p) try(ll_llRCE(p, N_SA_RA, N_SA_RB, N_SB_RA,N_SB_RB, nRatings, nCond), silent = TRUE))
+                  function(p) try(ll_RCE(p, N_SA_RA, N_SA_RB, N_SB_RA,N_SB_RB, nRatings, nCond), silent = TRUE))
     logL <- as.numeric(logL)
     inits <- inits[order(logL),]
     inits <- inits[1:nInits,]