R/Test_Null_Hypothesis_that_all_modalities_are_same.R

In BayesianFROC: FROC Analysis by Bayesian Approaches

#' @title Test the Null hypothesis that all modalities are same
#' @description
#'  Test null hypothesis that all modalities
#'  have same observer performance ablity,
#'  using Bayes factor.
#'
#' @details From input data (variable: \code{dataList}), the two objects
#' of class  \strong{\emph{\code{stanfit}}}
#'  are created. one is fitted to the null hypothesis model and
#'  the another one representing
#'  alternative hypothesis.
#'  These two  \strong{\emph{\code{stanfit}}}.
#'  objects are compared by the Bayes factor.
#'
#' @inheritParams fit_Bayesian_FROC
#' @param dataList MRMC is the  only case in which the function is available for this function.
#'
#' @return none
#' @export
#'
#@examples
# \dontrun{
#
#  Test_Null_Hypothesis_that_all_modalities_are_same(BayesianFROC::dd)
#
#  }#dontrun




Test_Null_Hypothesis_that_all_modalities_are_same <- function(
  dataList,
  ite =1111,
  cha =1,
  summary = FALSE
){


fitH0 <- fit_Bayesian_FROC( ite  = ite, summary = summary,  cha = cha, dataList = dataList , Null.Hypothesis = TRUE)
fitH1 <- fit_Bayesian_FROC( ite  = ite, summary = summary,  cha = cha, dataList = dataList , Null.Hypothesis = FALSE)



message("\n* Null model \n")
H0 <- bridgesampling::bridge_sampler(fitH0, method = "normal", silent = TRUE)
print(H0)

message("\n* Alternative model \n")
H1 <- bridgesampling::bridge_sampler(fitH1, method = "normal", silent = TRUE)
print(H1)

message("\n* Test the Null hypothesis that all modalities are same.\n")
BF10 <- bridgesampling::bf( H1,H0)
print(BF10)

message("\n* If the number is greater, then we reject H0 with more confidence.")
}#function