Description Usage Arguments Value Examples

View source: R/logisticfragility.R

Compute the fragility of a coefficient in a logistic regression for dichotomous outcomes, i.e. the number of removed observations it would take to make a significant-result non-significant. Uses the glm() function from the stats package.

1 2 | ```
logisticfragility(formula, data, covariate = "all.factors.default",
conf.level = 0.95, verbose = FALSE)
``` |

`formula` |
Model formula which will be evaluated by glm() |

`data` |
Dataframe with values for model forma, passed to glm() |

`covariate` |
Vector of covariates to find fragility index for. Default is all covariates in formula |

`conf.level` |
Significance level |

`verbose` |
Logical indicating if function will return verbose results or only fragility index |

If verbose is FALSE, returns a list with fragility indices for selected covariates. If verbose is TRUE, returns a list with p-values for each fragility index at each iteration of the algorithm.

1 2 3 4 5 6 7 |

fragilityindex documentation built on July 18, 2017, 1:02 a.m.

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