Hi there,
I´ve a question concerning the nnet package in the area of survival analysis:
what is the final value, which is computed to fit the model with the following
nnet-c
all:
net <- nnet(cat~x,
data=d,
size=2,
decay=0.1,
censored=TRUE,
maxit=20,
Wts=rep(0,22),
Hess=TRUE)
where cat is a matrix with a row for each record and one column for each
possible time-value and x another explanatory variable.
Something like that:
0 6 17 20 28 37
[1,] 0 0 0 0 0 1
[2,] 1 0 0 0 0 0
[3,] 0 0 1 1 1 1
[4,] 0 1 0 0 0 0
...
where 0,6,17,... are the time values and record 1 has an event in time period
37 and record 3 is censored in time period 20.
I tried to reproduce the final value with this term:
tmp <- rowSums(cat*summary(net)$fitted.values)
repFinalValue <- sum(-log(tmp))
but got the value 21.65438 instead of 21.71108. Is this only a rounding error
or what´s wrong with my formula?
My whole test example is printed below.
Thanks,
Andrea.
# Some tests ...
#
###############################################################################
require(survival)
require(nnet)
# training data
d <- matrix(nrow=20, ncol=3, dimnames=list(c(),c("time", "status", "x")))
d[,"time"] <- c(17,6,37,0,6,28,0,6,20,0,17,6,37,0,6,28,0,6,20,0)
d[,"status"] <- rep(c(0,1),5,each=2)
d[,"x"] <-
c(0.27,0.27,0.49,0.49,0.61,0.70,0.78,0.78,0.84,0.86,0.27,0.27,0.49,0.49,0.61,0.70,0.78,0.78,0.84,0.86)
# compute cat-variable
cat <- computeCatVector(d, "time", "status") # => a matrix with one row
for each row in d and a column for each distinct time value in d
# generated values for each
row in d:
# if status = 1 => 1 in the
time-Col, 0 otherwise
# if status = 0 => 1 from
the time-Col till the last column, 0 before
# here:
#0 6 17 20 28 37
#[1,] 0 0 0 0 0 1
#[2,] 1 0 0 0 0 0
#[3,] 0 0 1 1 1 1
#[4,] 0 1 0 0 0 0
#...
# nnet for survival analysis
net <- nnet(cat~x,
data=d,
size=2,
decay=0.1,
censored=TRUE,
maxit=20,
Wts=rep(0,22),
Hess=TRUE)
# reproduce the final value
tmp <- rowSums(cat*summary(net)$fitted.values)
repFinalValue <- sum(-log(tmp))
print(paste("Difference in finale value: mine vs. the nnet-final value:",
repFinalValue, "vs.",summary(net)$value))
# the function to calculate the cat-matrix from time and status information of
survival data
computeCatVector <- function(d, timeCol, statusCol){
# init some values
l <- length(unique(d[,timeCol]))
n <- length(d[,statusCol])
cols <- as.character(sort(unique(d[,timeCol])))
cat <- matrix(rep(0,l*n), ncol=l, dimnames=list(c(),cols))
for (i in 1:n) {
for (x in cols) {
# DS mit Ereignis
if(d[i,timeCol]==x & d[i,statusCol]==1){
cat[i,x] <- 1
}
# DS mit Zensur
if(as.numeric(as.character(d[i,timeCol]))<=as.numeric(x) &
d[i,statusCol]==0){
cat[i,x] <- 1
}
}
}
cat
}
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