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############################################################################################################################
# Function: ExpectedRejPower
# Argument: Test results (p-values) across multiple simulation runs (vector or matrix), statistic results (not used in this function),
# criterion parameter (Type I error rate and weigth).
# Description: Compute expected number of rejected hypothesis for the test results (vector of p-values or each column of the p-value matrix).
ExpectedRejPower = function(test.result, statistic.result, parameter) {
# Error check
if (is.null(parameter$alpha)) stop("Evaluation model: WeightedPower: alpha parameter must be specified.")
# Get the parameter
alpha = parameter$alpha
ntests = ncol(test.result)
weight = rep(1/ntests,ntests)
significant = (test.result <= alpha)
if (is.numeric(test.result))
# Only one test is specified and no weight is applied
power = mean(significant, na.rm = TRUE)
if (is.matrix(test.result)) {
# Weights are applied when two or more tests are specified
# Check if the number of tests equals the number of weights
marginal.power = colMeans(significant)
power = ntests * sum(marginal.power * weight, na.rm = TRUE)
}
return(power)
}
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