Power and Sample Size for One-Sample Poisson Rate Exact Test

Obtains the power given sample size or obtains the sample size given power for one-sample Poisson rate.

Usage

getDesignOneRateExact(
  beta = NA_real_,
  n = NA_real_,
  lambdaH0 = NA_real_,
  lambda = NA_real_,
  D = 1,
  alpha = 0.025
)

Arguments

beta

The type II error.

n

The total sample size.

lambdaH0

The Poisson rate under the null hypothesis.

lambda

The Poisson rate under the alternative hypothesis.

D

The average exposure per subject.

alpha

The one-sided significance level. Defaults to 0.025.

Value

A data frame containing the following variables:

• alpha: The specified significance level.

• attainedAlpha: The attained type I error of the exact test.

• power: The actual power of the exact test.

• n: The sample size.

• lambdaH0: The Poisson rate under the null hypothesis.

• lambda: The Poisson rate under the alternative hypothesis.

• D: The average exposure per subject.

• r: The critical value of the number of events for rejecting the null hypothesis. Reject H0 if Y >= r for upper-tailed test, and reject H0 if Y <= r for lower-tailed test.

Author

Kaifeng Lu, kaifenglu@gmail.com

Examples

# Example 1: power calculation
(design1 <- getDesignOneRateExact(
  n = 525, lambdaH0 = 0.049, lambda = 0.012,
  D = 0.5, alpha = 0.025))
#>   alpha attainedAlpha     power   n lambdaH0 lambda   D r
#> 1 0.025    0.01173728 0.9002103 525    0.049  0.012 0.5 5

# Example 2: sample size calculation
(design2 <- getDesignOneRateExact(
  beta = 0.2, lambdaH0 = 0.2, lambda = 0.3,
  D = 1, alpha = 0.05))
#>   alpha attainedAlpha     power   n lambdaH0 lambda D  r
#> 1  0.05    0.04267447 0.8078048 162      0.2    0.3 1 43