From 3ea7e286e18472e044f74f38a2798c4e53d5473f Mon Sep 17 00:00:00 2001
From: prise6 <vieille.francois@gmail.com>
Date: Mon, 15 Jun 2015 00:20:25 +0200
Subject: [PATCH] More details about sepsis.rdata

---
 .Rbuildignore       |   1 +
 R/data.R            |   4 +-
 data-raw/sepsis.R   |  42 ++++
 data-raw/sepsis.csv | 471 ++++++++++++++++++++++++++++++++++++++++++++
 data/sepsis.rdata   | Bin 6075 -> 6406 bytes
 5 files changed, 516 insertions(+), 2 deletions(-)
 create mode 100644 data-raw/sepsis.R
 create mode 100644 data-raw/sepsis.csv

diff --git a/.Rbuildignore b/.Rbuildignore
index 91114bf..4b3f9f2 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -1,2 +1,3 @@
 ^.*\.Rproj$
 ^\.Rproj\.user$
+^data-raw$
diff --git a/R/data.R b/R/data.R
index 0ff331c..2bee803 100644
--- a/R/data.R
+++ b/R/data.R
@@ -6,7 +6,7 @@
 #' \href{http://biopharmnet.com/wiki/Software_for_subgroup_identification_and_analysis}{SIDES
 #' method}.
 #' 
-#' \code{Sepsis} contains simulated data on 454 subjects with a binary outcome 
+#' \code{Sepsis} contains simulated data on 470 subjects with a binary outcome 
 #' survival, that stores survival status for patient after 28 days of treatment,
 #' value of 1 for subjects who died after 28 days and 0 otherwise. There are 11 
 #' covariates, listed below, all of which are numerical variables.
@@ -16,7 +16,7 @@
 #' 
 #' True subgroup is \emph{PRAPACHE <= 26 & AGE <= 49.80}
 #' 
-#' @format 454 patients and 13 variables.
+#' @format 470 patients and 13 variables.
 #' \describe{
 #'  \item{survival}{binary outcome}
 #'  \item{THERAPY}{1 for active treatment, 0 for control treatment}
diff --git a/data-raw/sepsis.R b/data-raw/sepsis.R
new file mode 100644
index 0000000..2207871
--- /dev/null
+++ b/data-raw/sepsis.R
@@ -0,0 +1,42 @@
+
+# Create sepsis data ------------------------------------------------------
+
+# Load some libraries
+library(VirtualTwins)
+library(randomForest) 
+
+# Sepsis is a csv file available in SIDES example to this address: 
+# http://biopharmnet.com/wiki/Software_for_subgroup_identification_and_analysis
+# type ?sepsis to see details
+# I downloaded zip file and extract the sepsis.csv in data-raw folder. 
+sepsis.csv <- read.csv(file = "data-raw/sepsis.csv", na.strings = ".")
+
+# Check data
+str(sepsis.csv)
+
+# Count NA's
+sum(is.na(sepsis.csv))
+# No NA's in outcome
+sum(is.na(sepsis.csv$survival))
+
+# For futures computation i need to impute missing values
+# I use random forest imputation with randomForest package with simple parameters
+# I need to make survival field as factor
+sepsis.csv$survival <- factor(sepsis.csv$survival, levels = 0:1) 
+sepsis.imp <- with(sepsis.csv, rfImpute(y = survival, x = sepsis.csv[, -1], iter = 5, ntree = 500))
+str(sepsis.imp)
+
+# Change THERAPY levels in 0/1 and type will be numeric
+sepsis.imp$THERAPY <- with(sepsis.csv, ifelse(THERAPY == "control", 0, 1))
+
+# Change survival into numeric values
+sepsis.imp$survival <- as.numeric(as.character(sepsis.imp$survival))
+
+# Check data
+sepsis <- formatRCTDataset(sepsis.imp, "survival", "THERAPY", T)
+
+# Save file into data folder
+save(sepsis, file = "data/sepsis.rdata")
+
+# End.
+
diff --git a/data-raw/sepsis.csv b/data-raw/sepsis.csv
new file mode 100644
index 0000000..8cbe9b6
--- /dev/null
+++ b/data-raw/sepsis.csv
@@ -0,0 +1,471 @@
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diff --git a/data/sepsis.rdata b/data/sepsis.rdata
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