getDesignUnorderedMultinom {lrstat} | R Documentation |
Power and sample size for unordered multi-sample multinomial response
Description
Obtains the power given sample size or obtains the sample size given power for the chi-square test for unordered multi-sample multinomial response.
Usage
getDesignUnorderedMultinom(
beta = NA_real_,
n = NA_real_,
ngroups = NA_integer_,
ncats = NA_integer_,
pi = NA_real_,
allocationRatioPlanned = NA_integer_,
rounding = TRUE,
alpha = 0.05
)
Arguments
beta |
The type II error. |
n |
The total sample size. |
ngroups |
The number of treatment groups. |
ncats |
The number of categories of the multinomial response. |
pi |
The matrix of response probabilities for the treatment groups.
It should have |
allocationRatioPlanned |
Allocation ratio for the treatment groups. |
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 designUnorderedMultinom
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. -
ngroups
: The number of treatment groups. -
ncats
: The number of categories of the multinomial response. -
pi
: The response probabilities for the treatment groups. -
effectsize
: The effect size for the chi-square test. -
allocationRatioPlanned
: Allocation ratio for the treatment groups. -
rounding
: Whether to round up sample size.
Author(s)
Kaifeng Lu, kaifenglu@gmail.com
Examples
(design1 <- getDesignUnorderedMultinom(
beta = 0.1, ngroups = 3, ncats = 4,
pi = matrix(c(0.230, 0.320, 0.272,
0.358, 0.442, 0.154,
0.142, 0.036, 0.039),
3, 3, byrow = TRUE),
allocationRatioPlanned = c(2, 2, 1),
alpha = 0.05))