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.
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