GEEaSPU {aSPU} | R Documentation |
It gives p-values of the GEESPU tests and GEEaSPU test.
GEEaSPU(
traits,
geno,
Z = NULL,
model = c("binomial", "gaussian"),
gamma = c(1:8, Inf),
n.sim = 1000,
corstr = "independence"
)
traits |
trait matrix. The row for individuals and the column for traits. |
geno |
A matrix of genetic information. |
Z |
covariates. |
model |
Use "gaussian" for a quantitative trait, and use "binomial" for a binary trait. |
gamma |
power used in GEEaSPU test. A vector of the powers. |
n.sim |
number of simulations. |
corstr |
a character string specifying the correlation structure. The following are permitted: "independence", "fixed", "stat_M_dep", "non_stat_M_dep", "exchangeable", "AR-M" and "unstructured" |
p-values for the GEE-SPU and GEE-aSPU test.
Junghi Kim, Wei Pan and Il-Youp Kwak
Yiwei Zhang, Zhiyuan Xu, Xiaotong Shen, Wei Pan (2014) Testing for association with multiple traits in generalized estimation equations, with application to neuroimaging data. Neuroimage. 96:309-25
traits <- matrix(rnorm(100*5, 0,1), ncol=5)
Z <- rnorm(100, 2, 0.5)
geno <- rbinom(100, 2, 0.5)
out <- GEEaSPU(traits, geno, Z = NULL, model = "gaussian",
gamma = c(1:8,Inf), n.sim = 100)