dPvalAggregate is supposed to aggregate a input matrix p-values
into a vector of aggregated p-values. The aggregate operation is
applied to each row of input matrix, each resulting in an aggregated
p-value. The method implemented can be based on the order statistics of
p-values or according to Fisher's method or Z-transform method.
dPvalAggregate(
pmatrix,
method = c("orderStatistic", "fishers", "Ztransform", "logistic"),
order = ncol(pmatrix),
weight = rep(1, ncol(pmatrix))
)a data frame or matrix of p-values
the method used. It can be either "orderStatistic" for the method based on the order statistics of p-values, or "fishers" for Fisher's method (summation of logs), or "Ztransform" for Z-transform test (summation of z values, Stouffer's method) and the weighted Z-test, or "logistic" for summation of logits
an integeter specifying the order used for the aggregation according to the order statistics of p-values
a vector specifying the weights used for the aggregation according to Z-transform method
ap: a vector with the length nrow(pmatrix), containing
aggregated p-values
# NOT RUN {
# 1) generate an iid uniformly-distributed random matrix of 1000x3
pmatrix <- cbind(runif(1000), runif(1000), runif(1000))
# 2) aggregate according to the order statistics
ap <- dPvalAggregate(pmatrix, method="orderStatistic")
# 3) aggregate according to the Fisher's method
ap <- dPvalAggregate(pmatrix, method="fishers")
# 4) aggregate according to the Z-transform method
ap <- dPvalAggregate(pmatrix, method="Ztransform")
# 5) aggregate according to the logistic method
ap <- dPvalAggregate(pmatrix, method="logistic")
# }
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