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Power and Sample Size for One-Way ANOVA Contrast

Source: R/getDesignMeans.R
getDesignANOVAContrast.Rd

Obtains the power and sample size for a single contrast in one-way analysis of variance.

Usage

getDesignANOVAContrast(
  beta = NA_real_,
  n = NA_real_,
  ngroups = 2,
  means = NA_real_,
  stDev = 1,
  contrast = NA_real_,
  meanContrastH0 = 0,
  allocationRatioPlanned = NA_real_,
  rounding = TRUE,
  alpha = 0.025
)

Arguments

beta

The type II error.

n

The total sample size.

ngroups

The number of treatment groups.

means

The treatment group means.

stDev

The common standard deviation.

contrast

The coefficients for the single contrast.

meanContrastH0

The mean of the contrast under the null hypothesis.

allocationRatioPlanned

Allocation ratio for the treatment groups. It has length ngroups - 1 or ngroups. If it is of length ngroups - 1, then the last treatment group will assume value 1 for allocation ratio.

rounding

Whether to round up sample size. Defaults to 1 for sample size rounding.

alpha

The one-sided significance level. Defaults to 0.025.

Value

An S3 class designANOVAContrast object with the following components:

  • power: The power to reject the null hypothesis for the treatment contrast.

  • alpha: The one-sided significance level.

  • n: The number of subjects.

  • ngroups: The number of treatment groups.

  • means: The treatment group means.

  • stDev: The common standard deviation.

  • contrast: The coefficients for the single contrast.

  • meanContrastH0: The mean of the contrast under the null hypothesis.

  • meanContrast: The mean of the contrast under the alternative hypothesis.

  • effectsize: The effect size.

  • allocationRatioPlanned: Allocation ratio for the treatment groups.

  • rounding: Whether to round up sample size.

Author

Kaifeng Lu, kaifenglu@gmail.com

Examples


(design1 <- getDesignANOVAContrast(
  beta = 0.1, ngroups = 4, means = c(1.5, 2.5, 2, 0),
  stDev = 3.5, contrast = c(1, 1, 1, -3),
  allocationRatioPlanned = c(2, 2, 2, 1),
  alpha = 0.025))
#>   alpha     power   n ngroups stDev meanContrastH0 meanContrast effectsize
#> 1 0.025 0.9002752 265       4   3.5              0            6 0.03998334