modified funnelPlot function to accept session hash as data parameter

R/funnelPlot.R

@@ -1,60 +1,60 @@
-#' @title Funnel plot
-#' @description
-#' Using metafor package to create a funnel plot.
-#' @param yi
-#' A \code{string} of the variable which holds the vector of length k with the observed effect sizes or outcomes in the selected dataset (d)
-#' @param vi
-#' A \code{string} of the variable which holds the vector of length k with the corresponding sampling variances in the selected dataset (d)
-#' @param d
-#' A \code{string} representing the dataset name that should be used for fitting.
-#' @param effectName
-#' A \code{string} representing the effect name that should be printed as label. defaults to "Effect"
-#' @param measure
-#' A character string indicating underlying summary measure.
-#' @return
-#' returns a Funnel plot for the given dataset
-#' @author Robert Studtrucker
-#' @export
-funnelPLot <- function(yi,vi,measure,d,peer="no", effectName="Effect") {
-
-  requireNamespace("metafor")
-
-  #load the in variable d defined dataset from the package
-  dat <- checkData(d)
-  checkParameter(dat,c(yi,vi,"r_peer"))
-
-  # Filtern nach veröffentlichten Studien wenn in der Anwendung ausgewählt (peer reviewed yes/no)
-  # Per default werden alle Studien mit einbezogen
-  if(peer == "yes"){
-    filtered_dat <- subset(dat,r_peer=="yes")
-  }else{
-    filtered_dat<-dat
-  }
-
-  if(measure == "COR") {
-    # z-standardisierte Daten erstellen
-    temp_dat <- metafor::escalc(measure="ZCOR", ri=filtered_dat[,yi], vi=filtered_dat[,vi], ni=filtered_dat[,"o_ni"], data=filtered_dat, var.names=c("o_zcor","o_zcor_var"))
-
-    # Modell berechnen
-    rma_model <- metafor::rma.uni(temp_dat[,"o_zcor"],temp_dat[,"o_zcor_var"], measure="ZCOR")
-
-    RTest <-metafor::regtest(x=rma_model)
-    metafor::funnel(rma_model, yaxis="sei") # 'label'
-    metafor::funnel(rma_model, level=c(90, 95, 99), shade=c("white", "orange", "red"), refline=0, legend=TRUE)
-    gc() # Force R to release memory it is no longer using
-
-    return(RTest)
-
-  }else{
-    rma_model <- metafor::rma.uni(yi=filtered_dat[,yi],vi=filtered_dat[,vi],measure=measure)
-    RTest <-metafor::regtest(x=rma_model)
-
-    metafor::funnel(rma_model, yaxis="sei") # 'label'
-    metafor::funnel(rma_model, level=c(90, 95, 99), shade=c("white", "orange", "red"), refline=0, legend=TRUE)
-    gc() # Force R to release memory it is no longer using
-
-    return(RTest)
-  }
-
-
-}
+#' @title Funnel plot
+#' @description
+#' Using metafor package to create a funnel plot.
+#' @param yi
+#' A \code{string} of the variable which holds the vector of length k with the observed effect sizes or outcomes in the selected dataset (d)
+#' @param vi
+#' A \code{string} of the variable which holds the vector of length k with the corresponding sampling variances in the selected dataset (d)
+#' @param d
+#' A \code{string} representing the dataset name that should be used for fitting.
+#' @param effectName
+#' A \code{string} representing the effect name that should be printed as label. defaults to "Effect"
+#' @param measure
+#' A character string indicating underlying summary measure.
+#' @return
+#' returns a Funnel plot for the given dataset
+#' @author Robert Studtrucker
+#' @export
+funnelPLot <- function(yi,vi,measure,d,peer="no", effectName="Effect") {
+
+  requireNamespace("metafor")
+
+  #load the in variable d defined dataset from the package
+  dat <- d
+  checkParameter(dat,c(yi,vi,"r_peer"))
+
+  # Filtern nach veröffentlichten Studien wenn in der Anwendung ausgewählt (peer reviewed yes/no)
+  # Per default werden alle Studien mit einbezogen
+  if(peer == "yes"){
+    filtered_dat <- subset(dat,r_peer=="yes")
+  }else{
+    filtered_dat<-dat
+  }
+
+  if(measure == "COR") {
+    # z-standardisierte Daten erstellen
+    temp_dat <- metafor::escalc(measure="ZCOR", ri=filtered_dat[,yi], vi=filtered_dat[,vi], ni=filtered_dat[,"o_ni"], data=filtered_dat, var.names=c("o_zcor","o_zcor_var"))
+
+    # Modell berechnen
+    rma_model <- metafor::rma.uni(temp_dat[,"o_zcor"],temp_dat[,"o_zcor_var"], measure="ZCOR")
+
+    RTest <-metafor::regtest(x=rma_model)
+    metafor::funnel(rma_model, yaxis="sei") # 'label'
+    metafor::funnel(rma_model, level=c(90, 95, 99), shade=c("white", "orange", "red"), refline=0, legend=TRUE)
+    gc() # Force R to release memory it is no longer using
+
+    return(RTest)
+
+  }else{
+    rma_model <- metafor::rma.uni(yi=filtered_dat[,yi],vi=filtered_dat[,vi],measure=measure)
+    RTest <-metafor::regtest(x=rma_model)
+
+    metafor::funnel(rma_model, yaxis="sei") # 'label'
+    metafor::funnel(rma_model, level=c(90, 95, 99), shade=c("white", "orange", "red"), refline=0, legend=TRUE)
+    gc() # Force R to release memory it is no longer using
+
+    return(RTest)
+  }
+
+
+}

R/testFunctions.R

@@ -34,3 +34,5 @@ testpredParameter<-function(pred1){
     print(pred1)
   pred1["value"]
 }
+
+