Update manual

data-raw/sepsis.R

@@ -22,7 +22,9 @@ 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$survival, levels = 0:1) 
+sepsis.csv$survival <- factor(sepsis.csv$survival, levels = 0:1)
+# reproducibility:
+set.seed(123)
 sepsis.imp <- with(sepsis.csv, rfImpute(y = survival, x = sepsis.csv[, -1], iter = 5, ntree = 500))
 str(sepsis.imp)
 

man/VT.difft.Rd

@@ -10,8 +10,14 @@ A reference class to represent difference between twin1 and twin2
 \details{
 Difft are calculated depending on the favorable outcome chosen. It is the
 second level of the outcome. For example, if the outcome is 0 and 1, the
-favorable outcome is 1. Then, \deqn{difft_i = twin1_i - twin2_i IF T_i =
+favorable outcome is 1. Then, \deqn{difft_i = twin1_i - twin2_i if T_i = 1}
-1} \deqn{ difft_i = twin2_i - twin1_i IF T_i = 0}
+\deqn{ difft_i = twin2_i - twin1_i if T_i = 0}.
+So \emph{absolute} method is :
+\deqn{P(Y = 1 | T = 1) - P(Y = 1 | T =0)}
+So \emph{relative} method is :
+\deqn{P(Y = 1 | T = 1)/P(Y = 1 | T =0)}
+So \emph{absolute} method is :
+\deqn{logit(P(Y = 1 | T = 1)) - logit(P(Y = 1 | T =0))}
 }
 \section{Fields}{
 
@@ -22,6 +28,9 @@ favorable outcome is 1. Then, \deqn{difft_i = twin1_i - twin2_i IF T_i =
 
 \item{\code{twin2}}{vector of \eqn{E(Y|T = another treatment)}}
 
+\item{\code{method}}{Method available to compute difft : c("absolute", "relative",
+"logit"). Absolute is default value. See details.}
+
 \item{\code{difft}}{vector of difference between twin1 and twin2}
 }}
 \section{Methods}{
@@ -30,6 +39,7 @@ favorable outcome is 1. Then, \deqn{difft_i = twin1_i - twin2_i IF T_i =
 \item{\code{computeDifft()}}{Compute difference between twin1 and twin2. See details.}
 }}
 \seealso{
-\code{\link{VT.forest}}, \code{\link{VT.forest.one}}, \code{\link{VT.forest.double}}
+\code{\link{VT.forest}}, \code{\link{VT.forest.one}},
+  \code{\link{VT.forest.double}}
 }
 

man/VT.object.Rd

@@ -40,7 +40,7 @@ treatments.}
 
 \item{\code{getFormula()}}{Return formula : Y~T+X1+...+Xp. Usefull for cforest function.}
 
-\item{\code{getIncidences()}}{Return incidence table of data.}
+\item{\code{getIncidences(rule = NULL)}}{Return incidence table of data if rule set to NULL. Otherwise return incidence for the rule.}
 
 \item{\code{getX(interactions = T, trt = NULL)}}{Return predictors (T,X,X*T,X*(1-T)). Or (T,X) if interactions is FALSE.
 If trt is not NULL, return predictors for T = trt}

man/VT.tree.Rd

@@ -70,7 +70,7 @@ screening field}
 \item{\code{getInfos()}}{Return infos about tree}
 
 \item{\code{getRules(only.leaf = F, only.fav = F, tables = T, verbose = T,
-  compete = F)}}{Retrun subgroups discovered by the tree. See details.}
+  compete = F)}}{Return subgroups discovered by the tree. See details.}
 
 \item{\code{run(...)}}{Compute tree with rpart parameters}
 }}

man/sepsis.Rd

@@ -4,22 +4,17 @@
 \name{sepsis}
 \alias{sepsis}
 \title{Clinical Trial for Sepsis desease}
-\format{454 patients and 13 variables.
+\format{470 patients and 13 variables. \describe{ \item{survival}{binary
-\describe{
+  outcome} \item{THERAPY}{1 for active treatment, 0 for control treatment}
- \item{survival}{binary outcome}
+  \item{TIMFIRST}{Time from first sepsis-organ fail to start drug}
- \item{THERAPY}{1 for active treatment, 0 for control treatment}
+  \item{AGE}{Patient age in years} \item{BLLPLAT}{Baseline local platelets}
- \item{TIMFIRST}{Time from first sepsis-organ fail to start drug}
+  \item{blSOFA}{Sum of baselin sofa (cardiovascular, hematology,
- \item{AGE}{Patient age in years}
+  hepaticrenal, and respiration scores)} \item{BLLCREAT}{Base creatinine}
- \item{BLLPLAT}{Baseline local platelets}
+  \item{ORGANNUM}{Number of baseline organ failures}
- \item{blSOFA}{Sum of baselin sofa (cardiovascular, hematology, hepaticrenal, and respiration scores)}
+  \item{PRAPACHE}{Pre-infusion apache-ii score} \item{BLGCS}{Base GLASGOW
- \item{BLLCREAT}{Base creatinine}
+  coma scale score} \item{BLIL6}{Baseline serum IL-6 concentration}
- \item{ORGANNUM}{Number of baseline organ failures}
+  \item{BLADL}{Baseline activity of daily living score}
- \item{PRAPACHE}{Pre-infusion apache-ii score}
+  \item{BLLBILI}{Baseline local bilirubin} }}
- \item{BLGCS}{Base GLASGOW coma scale score}
- \item{BLIL6}{Baseline serum IL-6 concentration}
- \item{BLADL}{Baseline activity of daily living score}
- \item{BLLBILI}{Baseline local bilirubin}
-}}
 \source{
 \url{http://biopharmnet.com/wiki/Software_for_subgroup_identification_and_analysis}
 }
@@ -27,21 +22,25 @@
 data(sepsis)
 }
 \description{
-Simulated clinical trial with two groups treatment about sepsis desease. See details.
+Simulated clinical trial with two groups treatment about sepsis desease. See
+details.
 }
 \details{
 This dataset is taken from
 \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.
 
 Note that contrary to the original dataset used in SIDES, missing values have
-been imputed by random forest \code{(randomForest::rfImpute())}
+been imputed by random forest \code{(randomForest::rfImpute())}. See file
+data-raw/sepsis.R for more details.
 
-True subgroup is \emph{PRAPACHE <= 26 & AGE <= 49.80}
+True subgroup is \emph{PRAPACHE <= 26 & AGE <= 49.80}. \emph{NOTE:} This
+subgroup is defined with the \emph{lower} event rate (survival = 1) in
+treatement arm.
 }
 

man/vt.data.Rd

@@ -0,0 +1,28 @@
+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/object.wrapper.R
+\name{vt.data}
+\alias{vt.data}
+\title{Initialize virtual twins data}
+\usage{
+vt.data(dataset, outcome.field, treatment.field, interactions = TRUE, ...)
+}
+\arguments{
+\item{dataset}{data.frame representing RCT's}
+
+\item{outcome.field}{name of the outcome's field in \code{dataset}}
+
+\item{treatment.field}{name of the treatment's field in \code{dataset}}
+
+\item{interactions}{logical. If running VirtualTwins with treatment's
+interactions, set to TRUE (default value)}
+
+\item{...}{parameters of \code{\link{VT.object}}}
+}
+\value{
+\code{VT.object}
+}
+\description{
+\code{vt.data} is a wrapper of \code{\link{formatRCTDataset}} and
+\code{\link{VT.object}}.
+}
+