Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/permute_select_surv.R
Variable selection using the permutation test on several scores of importance: IIS
, DIIS
and DEPTH
.
1 2  permute_select_surv(xdata, Y.names, P.names, T.names, importance = "IIS", method = "R2",
Bag, args.rpart, args.parallel = list(numWorkers = 1), nperm = 50)

xdata 
The learning data frame 
Y.names 
A vector of the names of the two variables of interest (the timetoevent is follow by the event indicator) 
P.names 
The names of independant variables acting on the nonsusceptible population (the plateau) 
T.names 
The names of independant variables acting on the survival of the susceptible population 
importance 
The importance score to consider: either 
method 
The splitting method: either 
Bag 
The number of Bagging samples to consider 
args.rpart 
The improper survival tree parameters: a list of options that control details of the rpart algorithm.

args.parallel 
a list containing the number of parallel computing arguments: The number of workers, the type of parallelization to achieve, ... see 
nperm 
The number of permutation samples to consider for the permutation test 
Testing weither the importance score is null or not.
A list of five elements:
pvalperm1 
The permutation test Pvalues ranking in decreasing order 
pvalperm2 
The permutation test Pvalues ranking in decreasing order considering an approximate gaussian distribution under the null hypothesis 
pvalKS 
The KolmogorovSmirnov Pvalues of the comparisons between the observed importance under the null hypothesis and a theoretical gaussian distribution 
IMPH1 
The observed importance score 
PERMH0 
A matrix with the importance scores for each permutation sample in each column 
Cyprien Mbogning and Philippe Broet
Mbogning, C. and Broet, P. (2016). Bagging survival tree procedure for variable selection and prediction in the presence of nonsusceptible patients. BMC bioinformatics, 17(1), 1.
1 2 3 4 5 6 7 8 9 10 11 12 13  ## Not run:
myarg = list(cp = 0, maxcompete = 0, maxsurrogate = 0, maxdepth = 2)
Y.names = c("T3" ,"D3")
P.names = 'Z2'
T.names = c("Z1", paste("Z", 3:11, sep = ''))
mybag = 40
set.seed(5000)
data(burn)
resperm0 < permute_select_surv(xdata = burn, Y.names, P.names, T.names, method = "LR",
Bag = mybag, args.rpart = myarg, args.parallel = list(numWorkers = 1), nperm = 150)
## End(Not run)

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