GLMaSPU (version 1.0)

aSPU_apval: Asymptotic based Sum of Powered Score (SPU) tests and adaptive SPU (aSPU) test.

Description

It gives p-values of the SPU tests and aSPU test.

Usage

aSPU_apval(Y, X, cov = NULL, pow = c(1:6, Inf), resample = "boot", model = "gaussian", n.perm = 5000)

Arguments

Y

Response. It can be binary or continuous trait. A vector with length n (number of observations).

X

Genotype or other data; each row for a subject, and each column for a variable of interest. An n by p matrix (n: number of observations, p: number of predictors).

cov

Covariates. An n by q matrix (n: number of observations, q: number of covariates).

pow

Gamma set used in SPU test. A vector of the powers.

resample

Resample methods. "perm" for residual permutations; "boot" for parametric bootstrap.

model

corresponding to the Response. "gaussian" for a quantitative response; "binomial" for a binary response.

n.perm

number of permutations or bootstraps.

Value

A list object, Ts : test statistics for the SPU tests and the aSPU test. pvs : p-values for the SPU and aSPU tests.

References

Chong Wu, Gongjun Xu and Wei Pan, "An Adaptive test on high dimensional parameters in generalized linear models" (Submitted)

Examples

p = 200
n = 100
beta = c(1,3,3)
s = 0.15
non.zero = floor(p * s)
signal.r = 0.08
seed = 2
alpha = c(rep(signal.r,non.zero),rep(0,p-non.zero))
dat = generate_data(seed, n = n, p = p, beta = beta,alpha = alpha)
cov = dat$Z
X = dat$X
Y = dat$Y
aSPU_apval(Y, X, cov = cov, pow = c(1:6, Inf),resample = "perm", model = "gaussian",  n.perm = 1000)
# The p-values are similar to the resample based one