View source: R/getDesignProportions.R
| getDesignRiskRatioExactEquiv | R Documentation |
Obtains the power given sample size or obtains the sample size given power for exact unconditional test of equivalence in risk ratio.
getDesignRiskRatioExactEquiv(
beta = NA_real_,
n = NA_real_,
riskRatioLower = NA_real_,
riskRatioUpper = NA_real_,
pi1 = NA_real_,
pi2 = NA_real_,
allocationRatioPlanned = 1,
alpha = 0.05
)
beta |
The type II error. |
n |
The total sample size. |
riskRatioLower |
The lower equivalence limit of risk ratio. |
riskRatioUpper |
The upper equivalence limit of risk ratio. |
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 significance level for each of the two one-sided tests. Defaults to 0.05. |
A data frame with the following variables:
alpha: The specified significance level for each of the two
one-sided tests.
attainedAlpha: The attained significance level.
power: The power.
n: The sample size.
riskRatioLower: The lower equivalence limit of risk ratio.
riskRatioUpper: The upper equivalence limit of risk ratio.
pi1: The assumed probability for the active treatment group.
pi2: The assumed probability for the control group.
riskRatio: The risk ratio.
allocationRatioPlanned: Allocation ratio for the active
treatment versus control.
zstatRiskRatioLower: The efficacy boundaries on the
z-test statistic scale for the one-sided null hypothesis on the
lower equivalence limit.
zstatRiskRatioUpper: The efficacy boundaries on the
z-test statistic scale for the one-sided null hypothesis on the
upper equivalence limit.
Kaifeng Lu, kaifenglu@gmail.com
getDesignRiskRatioExactEquiv(
n = 200, riskRatioLower = 0.8, riskRatioUpper = 1.25,
pi1 = 0.775, pi2 = 0.775, alpha = 0.05)
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