Merge pull request #501 from OHDSI/recalibration_docs

fix docs in recalibration code and add model output to recalibratePlpRefit

R/EvaluationSummary.R

@@ -451,11 +451,14 @@ averagePrecision <- function(prediction){
 }
 
 
-
-calibrationInLarge <- function(prediction){
+#' Calculate the calibration in large
+#' @param prediction            A prediction dataframe
+#' @return data.frame with meanPredictionRisk, observedRisk, and N
+#' @keywords internal
+calibrationInLarge <- function(prediction) {
 
   result <- data.frame(meanPredictionRisk = mean(prediction$value),
-    observedRisk = sum(prediction$outcomeCount)/nrow(prediction),
+    observedRisk = sum(prediction$outcomeCount) / nrow(prediction),
     N = nrow(prediction)
   )
 

R/Glm.R

@@ -25,7 +25,7 @@
 #' @param data An object of type \code{plpData} - the patient level prediction
 #' data extracted from the CDM.
 #' @param cohort The population dataframe created using
-#' /code{createStudyPopulation} who will have their risks predicted or a cohort
+#' \code{createStudyPopulation} who will have their risks predicted or a cohort
 #' without the outcome known
 #' @export
 #' @return A dataframe containing the prediction for each person in the 
@@ -75,7 +75,7 @@ predictGlm <- function(plpModel, data, cohort) {
 #' PatientLevelPrediction package.
 #' @param coefficients A dataframe containing two columns, coefficients and
 #' covariateId, both of type numeric. The covariateId column must contain
-#' valid covariateIds that match those used in the /code{FeatureExtraction}
+#' valid covariateIds that match those used in the \code{FeatureExtraction}
 #' package.
 #' @param intercept A numeric value representing the intercept of the model.
 #' @param finalMapping A string representing the final mapping from the 

R/Plotting.R

@@ -1259,14 +1259,14 @@ plotNetBenefit <- function(plpResult,
     }
 
     plots[[i]] <- ggplot2::ggplot(data = nbData, ggplot2::aes(x = .data$threshold)) +
-      ggplot2::geom_line(ggplot2::aes(y = treatAll, color = "Treat All", linetype = "Treat All")) +
-      ggplot2::geom_line(ggplot2::aes(y = treatNone, color = "Treat None", linetype = "Treat None")) +
-      ggplot2::geom_line(ggplot2::aes(y = netBenefit, color = "Net Benefit", linetype = "Net Benefit")) +
+      ggplot2::geom_line(ggplot2::aes(y = .data$treatAll, color = "Treat All", linetype = "Treat All")) +
+      ggplot2::geom_line(ggplot2::aes(y = .data$treatNone, color = "Treat None", linetype = "Treat None")) +
+      ggplot2::geom_line(ggplot2::aes(y = .data$netBenefit, color = "Net Benefit", linetype = "Net Benefit")) +
       ggplot2::scale_color_manual(
         name = "Strategies",
         values = c(
-          "Net Benefit" = "blue",
-          "Treat All" = "red",
+          "Model" = "blue",
+          "Treat all" = "red",
           "Treat None" = "brown"
         )
       ) +
@@ -1290,7 +1290,7 @@ plotNetBenefit <- function(plpResult,
 
   if (!is.null(saveLocation)) {
     if (!dir.exists(saveLocation)) {
-      dir.create(saveLocation, recursive = T)
+      dir.create(saveLocation, recursive = TRUE)
     }
     ggplot2::ggsave(file.path(saveLocation, fileName), plot, width = 5, height = 4.5, dpi = 400)
   }