72 lines
2.5 KiB
R
72 lines
2.5 KiB
R
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#' Naive Concordance
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#'
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#' Used to calculate a concordance index error. The user needs to supply a list
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#' of mortalities, with each item in the list being a vector for the
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#' corresponding event. To calculate mortalities a user should look to
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#' \code{\link{extractMortalities}}.
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#'
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#' @return A vector of 1 minus the concordance scores, with each element
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#' corresponding to one of the events. To be clear, the lower the score the
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#' more accurate the model was.
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#'
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#' @param responses A list of responses corresponding to the provided
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#' mortalities; use \code{\link{CR_Response}}.
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#' @param predictedMortalities A list of mortality vectors; each element of the
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#' list should correspond to one of the events in the order of event 1 to J,
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#' and should be a vector of the same length as responses.
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#' @export
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#' @references Section 3.2 of Wolbers, Marcel, Paul Blanche, Michael T. Koller,
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#' Jacqueline C M Witteman, and Thomas A Gerds. 2014. “Concordance for
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#' Prognostic Models with Competing Risks.” Biostatistics 15 (3): 526–39.
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#' https://doi.org/10.1093/biostatistics/kxt059.
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#'
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#' @examples
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#' data <- data.frame(delta=c(1,1,0,0,2,2), T=1:6, x=1:6)
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#'
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#' model <- train(CR_Response(delta, T) ~ x, data, ntree=100, numberOfSplits=0, mtry=1, nodeSize=1)
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#'
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#' newData <- data.frame(delta=c(1,0,2,1,0,2), T=1:6, x=1:6)
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#' predictions <- predict(model, newData)
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#'
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#' mortalities <- list(
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#' extractMortalities(predictions, 1, 6),
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#' extractMortalities(predictions, 2, 6)
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#' )
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#'
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#' naiveConcordance(CR_Response(newData$delta, newData$T), mortalities)
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#'
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naiveConcordance <- function(responses, predictedMortalities){
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if(is.null(responses)){
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stop("responses cannot be null")
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}
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if(is.null(predictedMortalities)){
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stop("predictedMortalities cannot be null")
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}
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if(!is.list(predictedMortalities)){
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stop("predictedMortalities must be a list")
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}
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responseList = responses$javaObject
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responseLength = .jcall(responseList, "I", "size")
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events = as.integer(1:length(predictedMortalities))
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concordances = numeric(length(predictedMortalities))
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for(event in events){
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if(length(predictedMortalities[[event]]) != responseLength){
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stop("Every mortality vector in predictedMortalities must be the same length as responses")
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}
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# Need to turn predictedMortalities into an array of doubles
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mortality = .jarray(predictedMortalities[[event]], "D")
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concordances[event] = 1 - .jcall(.class_CompetingRiskUtils, "D", "calculateConcordance", responseList, mortality, event)
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}
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return(concordances)
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}
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