logisticfragility: Logistic Fragility Function

In fragilityindex: Fragility Index

Description

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.

Usage

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

Arguments

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

Value

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.

Examples

# Import and format example data
mydata <- read.csv("https://stats.idre.ucla.edu/stat/data/binary.csv")
mydata$rank <- factor(mydata$rank)

logisticfragility(admit ~ gre + gpa + rank, data = mydata, covariate="gpa", verbose = TRUE)

logisticfragility(admit ~ gre + gpa + rank, data = mydata)

fragilityindex documentation built on May 1, 2019, 10:27 p.m.