permute_select_surv {iBST} | R Documentation |
Variable selection using the permutation test on several scores of importance: IIS
, DIIS
and DEPTH
.
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 time-to-event is follow by the event indicator) |
P.names |
The names of independant variables acting on the non-susceptible 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 P-values ranking in decreasing order |
pvalperm2 |
The permutation test P-values ranking in decreasing order considering an approximate gaussian distribution under the null hypothesis |
pvalKS |
The Kolmogorov-Smirnov P-values 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.
## 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 <- suppressWarnings(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)