Computes association statistics, the first four moments of the trend statistic A under permutation, and p-values based on the Beta density approximation.

MCC is a method which can measure association between rows of a matrix with a single response vector. The method uses a parametric approximation to permutation of the correlation coefficient. It is very accurate, often to p-values of 10^{-8} or smaller.

getAkmoment
(Package: mcc) :
Four moments of Pearson correlation under permutation

The Pearson Correlation Coefficient can be derived by the correlation of scared feature matrix and clinical response. This function provides the first four moments under permutation of the scaled pearson correlation coefficient. In order to simplify the computation of moments summed over strata, an internal offset is applied to center each stratum levels.

getAmoment
(Package: mcc) :
Four moments of Pearson correlation under permutation given covariates

The Pearson Correlation Coefficient can be derived by the correlation of scared feature matrix and clinical response. This function provides the first four moments under permutation of the scaled pearson correlation coefficient. Different from function getAkmoment, this function can handle covariate. For convenience in later functions, both central and noncentral moments are outputted.