# R/prepare.R In nparsurv: Nonparametric Tests for Main Effects, Simple Effects and Interaction Effect in a Factorial Design with Censored Data

```#############################################
# Prepare Data-                             #
# Divide into Subsets by the Two Factors     #
#############################################

#=================================================================================================================

# input:   data frame of the form (time,status, factor1, factor2)

# output:  list of :
#             - whole data set with a new variable cell, which indicates in which cell an observation is
#             - subset for each cell  (time,event,factor1, factor2, cell)

#=================================================================================================================

prepare <- function(data){

data <- na.omit(data)
# save the levels of the two factor variables and their length and number of observations
levels3 <- levels(data[,3])
a       <- length(levels3)
levels4 <- levels(data[,4])
b       <- length(levels4)
n       <- dim(data)[1]

# a vector to save which cell the observation belongs to
cell       <- rep(0,n)
cell_count <- 1
data       <- cbind(data, cell)

# assign the cell level to each individual

for ( j in 1:a ) {

# look trough all levels of A
for ( k in 1:b ) {

# look through all levels of B
for (i in 1:n ) {

if (data[i, 3] == levels3[j] & data[i, 4] == levels4[k]) {
data\$cell[i] <- cell_count
}

}
cell_count<-cell_count+1
}
}

data\$cell <- as.factor(data\$cell)
result    <- list(data)

for (i in 1:max(as.numeric(data\$cell)) ) {
datahelp <- data[data\$cell == i, ]
result   <- c(result, list(datahelp))
}

return (result)
}
```

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nparsurv documentation built on May 2, 2019, 3:27 a.m.