BlindingIndex: Computes a simple index for blinding in randomized clinical trials.

Description

This routine takes the entries from a 2x2 table as the arguments and returns the estimate for the difference of the probabilities p_A-p_B along with the Wilson-CI. It also finds a p-value dual to the Wilson method. For more details, see the paper "A simple blinding index for randomized controlled trials" by Petroff, Bacak, Dagres, Dilk and Wachter, which has been submitted for publication.

Usage

BlindingIndex(
  n_AA,
  n_BA,
  n_AB,
  n_BB,
  tolerance = 1e-12,
  switch_point = 1e-12,
  conf.level = 0.95
)

Value

est: Estimate
lwr.ci: Lower end of CI
upr.ci: Upper end of CI
p.value: p-value dual to the Wilson CI method
z: z-value corresponding to the p-value

Arguments

n_AA

Number of patients in Group A guessing that they are in Group A. A non-negative number, usually an integer.

n_BA

Number of patients in Group A guessing that they are in Group B. A non-negative number, usually an integer.

n_AB

Number of patients in Group B guessing that they are in Group A. A non-negative number, usually an integer.

n_BB

Number of patients in Group B guessing that they are in Group B. A non-negative number, usually an integer.

Alternatively, one can pass the first four arguments as a single 2x2 table, that is, as.table(cbind(c(n_AA, n_BA), c(n_AB, n_BB))).

tolerance

Tolerance for the `stats::uniroot' function.

switch_point

A technical detail. A (very small) positive number.

conf.level

confidence level.

Examples

Run this code

BlindingIndex(50, 50, 50, 50)

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