Permutation_Test: Permutation Test

In GSSE: Genotype-Specific Survival Estimation

Description

Permutation test for the Sieve-NPMLE switch method with null hypothesis H_0: F_carr = F_non and alternative hypothesis H_1: F_carr is not equal to F_non.

Usage

Permutation_Test (Grid, F_carr, F_non, OY, ODelta, Op0G, nperm)

Arguments

Grid	time points at which the distribution function values are estimated.
F_carr	a vector of distribution function values at given grid points of the carrier group.
F_non	a vector of distribution function values at given grid points of the non-carrier group.
OY	observed event times.
ODelta	observed indicators of right censoring.
Op0G	observed probability values of carrier and non-carrier groups.
nperm	replication number used in permutation.

Details

Technical details can be found in Wang et al. (2015).

Value

This function returns a list of prediction values for classes,

Test_Stat	value of the Kolmogorov-Smirnov statistic with observed data.
Pvalues	p-value of the permutation test.
Permutation.value	values of Kolmogorov-Smirnov statistics under all permutations.

References

Wang, Y., Liang, B., Tong, X., Marder, K., Bressman, S., Orr-Urtreger, A., Giladi, N. & Zeng, D. (2015). Efficient estimation of nonparametric genetic risk function with censored data. Biometrika, 102(3), 515-532.

See Also

test_stat() and Sieve_NPMLE_Switch().

Examples

data("Simulated_data");

OY = Simulated_data[,2];
ind = order(OY);
ODelta = Simulated_data[,3];
Op0G = Simulated_data[,4];

Y = OY[ind];
Delta = ODelta[ind];
p0G = Op0G[ind];

Grid = seq(0.2, 3.65, 0.05);
fix_t1 = c(0.288, 0.693, 1.390);
fix_t2 = c(0.779, 1.860, 3.650);
px = seq(0.1, 3, 0.1);

SieveNPMLE_result = Sieve_NPMLE_Switch( Y=Y, Delta=Delta, p0G=p0G,
                                        px=px, Grid=Grid, Knot=7,
                                        degree=3 );

Lambda_1.hat = cumsum( SieveNPMLE_result$lamb1.hat );
Lambda_2.hat = cumsum( SieveNPMLE_result$lamb2.hat );

F_carr_func = function(x){ 1 - exp( max( Lambda_1.hat[Y <= x] ) ) }
F_non_func  = function(x){ 1 - exp( max( Lambda_2.hat[Y <= x] ) ) }

F_carr = apply( matrix(px, ncol=1), 1, F_carr_func );
F_non = apply( matrix(px, ncol=1), 1, F_non_func );

# Permutation test #

Permutation_Test( Grid=Grid, F_carr=F_carr, F_non=F_non,
                  OY=OY, ODelta=ODelta, Op0G=Op0G,
                  nperm=10 );

GSSE documentation built on May 2, 2019, 12:40 p.m.