Description Usage Arguments Details Value Author(s) References See Also

Create a table of bootstrapped means and confidence intervals for all edges of a bootstrapped Joint Graphical Lasso model obtained through GroupNetworkBoot.

1 | ```
BootTable(BootOut)
``` |

`BootOut` |
The output from GroupNetworkBoot |

Summary table of the output of GroupNetworkBoot

`Var1` |
Nodes included in each edge |

`Var2` |
Nodes included in each edge |

`edges` |
Edge identifier |

`sample` |
sample value of each edge |

`boot.mean` |
mean of boostrapped values of each edge |

`ci.lb` |
lower bound of the .95 confidence interval |

`ci.ub` |
upper bound of the .95 confidence interval |

`boot.zero` |
proportion of bootstraps, in which an edge was estimated as equal to zero (i.e., 0= edge not estimated as zero throughout bootstraps; 1= edge estimated as zero in all bootstraps) |

`boot.pos` |
Proportion of bootstraps in which an edge was estimated as >0 (i.e., positive) |

`boot.neg` |
Proportion of bootstraps in which an edge was estimated as <0 (i.e., negative) |

`g` |
group in which the edge was estimated |

Nils Kappelmann <n.kappelmann@gmail.com>, Giulio Costantini

Epskamp, S., Borsboom, D., & Fried, E. I. (2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50(1), 195–212. https://doi.org/10.3758/s13428-017-0862-1 Danaher, P., Wang, P., & Witten, D. M. (2014). The joint graphical lasso for inverse covariance estimation across multiple classes. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 76(2), 373–397. https://doi.org/10.1111/rssb.12033

JGL, qgraph, parcor

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