power_Gamma {PASSED} | R Documentation |
Power Calculations for Test of Two Gamma Means
Description
Compute the power for a test of two sample means with Gamma distributions, or determine parameters to obtain a target power.
Usage
power_Gamma(n1 = NULL, n2 = NULL, power = NULL, sig.level = 0.05,
mu1 = NULL, mu2 = NULL, gmu1 = NULL, gmu2 = NULL, trials = 100,
M = 10000, equal.sample = TRUE, equal.shape = NULL, trace = FALSE)
Arguments
n1 |
sample size in group 1, or sample size in each group if equal.sample = TRUE |
n2 |
sample size in group 2 |
power |
power of test (1 minus Type II error probability) |
sig.level |
significance level (Type I error probability) |
mu1 |
arithmetic mean of group 1 |
mu2 |
arithmetic mean of group 2 |
gmu1 |
geometric mean of group 1 |
gmu2 |
geometric mean of group 2 |
trials |
number of trials in simulation |
M |
number of simulations used in CAT method, see Chang (2011) |
equal.sample |
equal sample sizes for two groups, see details |
equal.shape |
assume the shape parameters are equal for two groups, see details |
trace |
if positive, sample size and power are printed during the running of each simulation |
Details
Exactly one of the parameters n1
, n2
, and power
must be passed as NULL, and that parameter is determined from the others.
Notice that sig.level
has non-NULL defaults, so NULL must be explicitly passed if you want to compute it.
If equal.sample = TRUE
is used, N in output will denote the number in each group.
The equal shape parameter assumption will be tested automatically; otherwise it could be set manually with equal.shape
.
Value
Object of class "power.htest", a list of the arguments (including the computed one) augmented with method element.
References
Chang et al. (2011). Testing the equality of several gamma means: a parametric bootstrap method with applications. Computational Statistics, 26:55-76.
Examples
# Calculate power, equal sizes
power_Gamma(n1 = 50, mu1 = 1, mu2 = 1.5, gmu1 = 0.6, gmu2 = 0.6, M = 100)