aSPU_perm: Resample based Sum of Powered Score (SPU) tests and adaptive...

In GLMaSPU: An Adaptive Test on High Dimensional Parameters in Generalized Linear Models

Description

aSPU_perm returns p-values of the SPU tests and aSPU test.

Usage

aSPU_perm(Y, X, cov = NULL, resample = c("perm", "boot"),
  model = c("gaussian", "binomial"), pow = c(1:6, Inf), n.perm = 1000)

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

Wei Pan, Junghi Kim, Yiwei Zhang, Xiaotong Shen and Peng Wei (2014) A powerful and adaptive association test for rare variants, Genetics, 197(4), 1081-95

Examples

p = 200
n = 100
beta = c(1,3,3)
s = 0.15
signal.r = 0.08
non.zero = floor(p * s)
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_perm(Y, X, cov = cov, pow = c(1:6, Inf),resample = "perm", model = "gaussian",  n.perm = 1000)
# The p-values are similar to the asymptotic based one

GLMaSPU documentation built on May 2, 2019, 11:24 a.m.