getDesignRiskDiffExact: Power and Sample Size for Exact Unconditional Test for Risk...

In lrstat: Power and Sample Size Calculation for Non-Proportional Hazards and Beyond

Power and Sample Size for Exact Unconditional Test for Risk Difference

Description

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(s)

Kaifeng Lu, [e-mail]

Examples

# Superiority test

getDesignRiskDiffExact(n = 50, pi1 = 0.6, pi2 = 0.25, alpha = 0.025)


# Non-inferiority test

getDesignRiskDiffExact(beta = 0.2, riskDiffH0 = -0.3,
                       pi1 = 0.9, pi2 = 0.9, alpha = 0.025)

lrstat documentation built on Oct. 18, 2024, 9:06 a.m.