Description Usage Arguments Value Author(s) References Examples
The function GEE.approx.aSPU compute the p-values of aSPU test based on approximated Score vectors from GEE
1 2 |
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 |
P-values for SPU and aSPU test based on approximated Score vector from GEE
Zhiyuan (Jason) Xu, Yiwei Zhang and Wei Pan
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
1 2 3 4 | 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
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