getDesignTwoMultinom: Power and Sample Size for Difference in Two-Sample...

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

Power and Sample Size for Difference in Two-Sample Multinomial Responses

Description

Obtains the power given sample size or obtains the sample size given power for difference in two-sample multinomial responses.

Usage

getDesignTwoMultinom(
  beta = NA_real_,
  n = NA_real_,
  ncats = NA_integer_,
  pi1 = NA_real_,
  pi2 = NA_real_,
  allocationRatioPlanned = 1,
  rounding = TRUE,
  alpha = 0.05
)

Arguments

beta	The type II error.
n	The total sample size.
ncats	The number of categories of the multinomial response.
pi1	The prevalence of each category for the treatment group. Only need to specify the valued for the first ncats-1 categories.
pi2	The prevalence of each category for the control group. Only need to specify the valued for the first ncats-1 categories.
allocationRatioPlanned	Allocation ratio for the active treatment versus control. Defaults to 1 for equal randomization.
rounding	Whether to round up sample size. Defaults to 1 for sample size rounding.
alpha	The two-sided significance level. Defaults to 0.05.

Value

An S3 class designTwoMultinom object with the following components:

• power: The power to reject the null hypothesis.

• alpha: The two-sided significance level.

• n: The maximum number of subjects.

• ncats: The number of categories of the multinomial response.

• pi1: The prevalence of each category for the treatment group.

• pi2: The prevalence of each category for the control group.

• effectsize: The effect size for the chi-square test.

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

• rounding: Whether to round up sample size.

Author(s)

Kaifeng Lu, [e-mail]

Examples

(design1 <- getDesignTwoMultinom(
  beta = 0.1, ncats = 3, pi1 = c(0.3, 0.35),
  pi2 = c(0.2, 0.3), alpha = 0.05))

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