Description Usage Arguments Value Examples
Compare the bivariate CCIF of different failure typess by applying the technique of
permutation test. See bigtcr-package
.
1 2 | get.gap.pval(obs.y, event, v, tau = Inf, comp.event = c(1, 2), np = 1000,
Kt = function(x) { 1 })
|
obs.y |
Y: time to failure events or censoring |
event |
0: censored; 1, … J: type of failure events |
v |
Time to the first failure event (e.g. disease recurrence) |
tau |
Conditioning time τ under which the CCIF is defined |
comp.event |
Failure events for CCIF comparison |
np |
Number of permutations |
Kt |
A weight function that takes one parameter t and return the weight for t. Default weight function is constant 1 |
P-value of the hypothesis test H_0: H_j = H_k = … = H_l.
1 2 | gap.pval <- get.gap.pval(pancancer$obs.y, pancancer$min.type, pancancer$v,
tau=120, comp.event=c(1,2), np=20);
|
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