SBI (version 0.1.2)

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 Newcombe-Wilson-CI. It also finds a p-value dual to the Newcombe-Wilson method. For more details, see Petroff, Bacak, Dagres, Dilk, Wachter: A simple blinding index for randomized controlled trials. Contemp Clin Trials Commun. 2024 Nov 26;42:101393. doi: 10.1016/j.conctc.2024.101393. PMID: 39686958.

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

BlindingIndex(50, 50, 50, 50)