Description Usage Arguments Value Author(s) References Examples

Filters the network based on an r-value, alpha, adaptive alpha, bonferroni, false-discovery rate (FDR), or proportional density (fixed number of edges) value

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`data` |
Can be a dataset or a correlation matrix |

`a` |
When thresh = "alpha", "adaptive", and "bonferroni" an alpha threshold is applied (defaults to |

`thresh` |
Sets threshold. Defaults to "alpha".
Set to any value 0> |

`n` |
Number of participants in sample.
Defaults to the number of rows in the data.
If input is a correlation matrix, then n |

`normal` |
Should data be transformed to a normal distribution? Defaults to FALSE. Data is not transformed to be normal. Set to TRUE if data should be transformed to be normal (computes correlations using the cor_auto function) |

`na.data` |
How should missing data be handled?
For "listwise" deletion the |

`...` |
Additional arguments for fdrtool and adapt.a |

Returns a list containing:

`A` |
The filtered adjacency matrix |

`r.cv` |
The critical correlation value used to filter the network |

Alexander Christensen <[email protected]>

Strimmer, K. (2008).
fdrtool: A versatile R package for estimating local and tail area-based false discovery rates.
*Bioinformatics*, *24*, 1461-1462.
doi: 10.1093/bioinformatics/btn209

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AlexChristensen/NetworkToolbox documentation built on July 24, 2018, 7:01 a.m.

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