WaldTest <- function(Coef, Cov, Contrast, nullModel ="standN"){
# simple Wald test for: Contrast^T%*%beta = 0
#### nullModel: which null model to use to calculate p-value
Contrast = as.matrix(Contrast, ncol = 1)
se = rep(NA, nrow(Coef))
#for (i in 1:nrow(Coef)) {
for (i in seq_len(nrow(Coef))) {
if(!all(is.na(Cov[[i]]))){
tmp = Cov[[i]]
se[i] = sqrt( t(Contrast)%*%Cov[[i]]%*% Contrast)
}
}
lor = t(Contrast)%*%t(Coef)
stat = (t(Contrast)%*%t(Coef))/se
tmp.infer = DMRInfer(stat, nullModel = nullModel)
return(res = data.frame(logOR = as.numeric(lor),
lorSE = as.numeric(se),
stat = round(as.numeric(stat), 3),
pvalue = as.numeric(tmp.infer$pvalue),
padj = as.numeric(tmp.infer$padj)))
}
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