| power.free1way.test {stats} | R Documentation |
Power Calculations in Distribution-free Stratified One-Way Layouts
Description
Compute power of tests via simulation and approximation or determine parameters to obtain target power.
Usage
rfree1way(n, prob = NULL, alloc_ratio = 1,
blocks = ifelse(is.null(prob), 1, NCOL(prob)),
strata_ratio = 1, delta = 0, offset = 0,
link = c("logit", "probit", "cloglog", "loglog"))
power.free1way.test(n = NULL,
prob = if (is.null(n)) NULL else rep.int(1/n, n),
alloc_ratio = 1,
blocks = if (is.null(prob)) 1 else NCOL(prob),
strata_ratio = 1, delta = NULL, mu = 0, sig.level = 0.05,
power = NULL,
link = c("logit", "probit", "cloglog", "loglog"),
alternative = c("two.sided", "less", "greater"), nsim = 100,
seed = NULL, tol = .Machine$double.eps^0.25)
Arguments
n |
number of observations in the control group of the first block. |
prob |
an optional matrix defining the density of discrete controls for each block (in columns). |
alloc_ratio |
allocation ratio, a factor defining the number of
observations in each but the first group for the first block relative to
|
blocks |
number of blocks. |
strata_ratio |
stratification ratio, a factor defining the number of observations in each block relative to the first block. |
delta |
true effects comparing each group to the control group. |
offset |
a group-specific offset term, its length is recycled to the number of groups if necessary. |
link |
a character defining a link function and thus the model and
parameter interpretation. See |
alternative |
a character string specifying the alternative
hypothesis, must be one of |
mu |
a vector specifying optional parameters used to form the
null hypothesis. See |
sig.level |
significance level (Type I error probability). |
power |
power of test (1 minus Type II error probability). |
nsim |
number of simulations used to approximate the Hessian
evaluated at the true effects |
seed |
an object specifying if and how the random number generator
should be initialized, see |
tol |
numerical tolerance used in root finding, the default providing (at least) four significant digits. |
Details
The two functions use the same interface to sample from a specific
distribution-free semiparametric model (rfree1way) or to evaluate the
power of such a design (power.free1way.test). The latter function can
also be used to solve the power function for sample size or
effect. The power function relies on an simulation-based approximation of the
Hessian. This is much faster than simulations for estimating the power
directly, but less accurate.
Value
For power.free1way.test, an object of class power.htest, a list of the arguments
(including the computed one). A data
frame with simulated outcome values (y) for rfree1way with
variables groups and (optionally) blocks.
Examples
## make example reproducible
set.seed(29)
## sample from proportional odds model with 1:2 allocation
## based on odds ratio of 3, with sample sizes (15, 30)
x <- rfree1way(n = 15, delta = log(3), alloc_ratio = 2)
# Wilcoxon-Mann-Whitney rank sum test via classical stats interface
wilcox.test(y ~ groups, data = x, exact = FALSE, correct = FALSE)$p.value
# Identical p-value obtained from a proportional-odds model
summary(free1way(y ~ groups, data = x), test = "Permutation")$p.value
# approximate power for this test
power.free1way.test(n = 15, delta = log(3), alloc_ratio = 2)