Description Usage Arguments Value Examples
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.
1 2 | fragility.index(intervention_event, control_event, intervention_n, control_n,
conf.level = 0.95, verbose = FALSE, print.mat = FALSE)
|
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 |
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.
1 | fragility.index(15, 5, 40, 40)
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