GEE.approx.aSPU: The function GEE.approx.aSPU compute the p-values of aSPU...

In jasonzyx/APaSPU: Adaptive Sum of Powered Test (aSPU) Based on Approximated Score Vector

Description

The function GEE.approx.aSPU compute the p-values of aSPU test based on approximated Score vectors from GEE

Usage

GEE.approx.aSPU(dat, y, par, cov, groupID, corstr = "independence",
  family = "binomial", pow = c(1:8, Inf), B)

Arguments

dat,	the data table for analysis
y,	response name
par,	variables of interest for testing
cov,	covariates needed to be adjusted
groupID,	group ID name
corstr,	working correlation structure for GEE
family	type, common ones are "gaussian" and "binomial".
pow,	power integer candidates
B,	simulation number to calculate P-values

Value

P-values for SPU and aSPU test based on approximated Score vector from GEE

Author(s)

Zhiyuan (Jason) Xu, Yiwei Zhang and Wei Pan

References

Zhiyuan Xu, Wei Pan (2014) Approximate score-based testing with application to multivariate trait association analysis. Genetic Epidemiology. 39(6): 469-479.

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

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

Examples

data("exdat_GLMM")
gee.aSPU <- GEE.approx.aSPU(exdat_GLMM, "Y", paste0("X.",1:10), cov = NULL,
groupID = "ID",corstr="independence",family="binomial", B = 1000 )
gee.aSPU

jasonzyx/APaSPU documentation built on May 18, 2019, 5:55 p.m.