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

In ChongWu-Biostat/GLMaSPU: An Adaptive Test on High Dimensional Parameters in Generalized Linear Models

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.

Author(s)

Chong Wu and Wei Pan

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 = 0.02
seed = 1
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

ChongWu-Biostat/GLMaSPU documentation built on May 6, 2019, 11:18 a.m.