# Multiple testing correction procedure for ncpc()

### Description

This function is only for DDGraph with multiple testing correction enabled. The overall procedure is similar to
that described in (Li&Wang 2009). This is a helper function for `DDDataSet:ncpc()`

. The single P-value
of D-separation is substituted in the list of P-values, P-values adjusted and the resulting P-value after correction
in the context of other P-values reported.

### Usage

1 | ```
pValueAfterMultipleTesting(dsep, x, adjC.pvals.at.n, p.value.adjust.method)
``` |

### Arguments

`dsep` |
the conditional independence test result (of type |

`x` |
the index of the variables |

`adjC.pvals.at.n` |
the p values associated with the variables at size n of conditioning set (list [[n]] -> [pvals]) |

`p.value.adjust.method` |
the p value adjustment method (same as in p.adjust()) |

### Value

the p value after multiple test correction (if any)

### References

J. Li and Z. J Wang, "Controlling the false discovery rate of the association/causality structure learned with the PC algorithm" The Journal of Machine Learning Research 10 (2009): 475-514.