fragility.index: Fragility Index Calculation

In kippjohnson/fragilityindex: Fragility Index

Description

Compute the fragility index for a dichotomous outcome, i.e. the number of flipped outcomes between cases and control it would take to make a significant-result non-significant.

Usage

fragility.index(intervention_event, control_event, intervention_n, control_n,
  conf.level = 0.95, verbose = FALSE, print.mat = FALSE)

Arguments

intervention_event	Number of events in intervention group
control_event	Number of events in control group
intervention_n	Total number of patients in intervention group
control_n	Total number of patients in the control group
conf.level	Significance level
verbose	Logical indicating if function will return verbose results or only fragility index
print.mat	Logical indicating if 2x2 matrices should be printed for each iteration of algorithm

Value

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

Examples

fragility.index(15, 5, 40, 41, verbose = TRUE)

kippjohnson/fragilityindex documentation built on May 20, 2019, 10:23 a.m.