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Power and Sample Size for Exact Unconditional Test for Risk Difference

Source: R/getDesignProportions.R
getDesignRiskDiffExact.Rd

Obtains the power given sample size or obtains the sample size given power for exact unconditional test of risk difference.

Usage

getDesignRiskDiffExact(
  beta = NA_real_,
  n = NA_real_,
  riskDiffH0 = 0,
  pi1 = NA_real_,
  pi2 = NA_real_,
  allocationRatioPlanned = 1,
  alpha = 0.025
)

Arguments

beta

The type II error.

n

The total sample size.

riskDiffH0

The risk difference under the null hypothesis. Defaults to 0.

pi1

The assumed probability for the active treatment group.

pi2

The assumed probability for the control group.

allocationRatioPlanned

Allocation ratio for the active treatment versus control. Defaults to 1 for equal randomization.

alpha

The one-sided significance level. Defaults to 0.025.

Value

A data frame with the following variables:

  • alpha: The specified one-sided significance level.

  • attainedAlpha: The attained one-sided significance level.

  • power: The power.

  • n: The sample size.

  • riskDiffH0: The risk difference under the null hypothesis.

  • pi1: The assumed probability for the active treatment group.

  • pi2: The assumed probability for the control group.

  • allocationRatioPlanned: Allocation ratio for the active treatment versus control.

  • zstatRiskDiffBound: The critical value on the scale of score test statistic for risk difference.

  • pi2star: The response probability in the control group at which the critical value of the test statistic is attained.

Author

Kaifeng Lu, kaifenglu@gmail.com

Examples


# Superiority test

getDesignRiskDiffExact(n = 50, pi1 = 0.6, pi2 = 0.25, alpha = 0.025)
#>   alpha attainedAlpha     power  n riskDiffH0 pi1  pi2 allocationRatioPlanned
#> 1 0.025    0.02315239 0.6946112 50          0 0.6 0.25                      1
#>   zstatRiskDiffBound  pi2star
#> 1           2.039508 0.106221


# Non-inferiority test

getDesignRiskDiffExact(beta = 0.2, riskDiffH0 = -0.3,
                       pi1 = 0.9, pi2 = 0.9, alpha = 0.025)
#>   alpha attainedAlpha     power  n riskDiffH0 pi1 pi2 allocationRatioPlanned
#> 1 0.025    0.02433985 0.8672679 47       -0.3 0.9 0.9                      1
#>   zstatRiskDiffBound   pi2star
#> 1           2.057453 0.5125817