n_glm: Calculate sample size for a group comparison via generalized...

In skewsamp: Estimate Sample Sizes for Group Comparisons with Skewed Distributions

Description

Estimation of required sample size as given by Cundill & Alexander (2015).

Usage

n_glm(
  mean0,
  mean1,
  dispersion0,
  dispersion1,
  alpha,
  power,
  link_fun = function(mu) NULL,
  variance_fun = function(mu, dispersion) NULL,
  dmu_deta_fun = function(mu) NULL,
  q
)

Arguments

mean0	Mean in control group
mean1	Mean in treatment group
dispersion0	Dispersion parameter in control group
dispersion1	Dispersion parameter in treatment group.
alpha	Type I error rate
power	1 - Type II error rate
link_fun	function object, the link function to create the response η.
variance_fun	function object, function for computing the variance based on a mean and a dispersion parameter
dmu_deta_fun	function object, derivative of the original mean with respect to the link: dμ / dη.
q	Number between 0 and 1, the proportion of observations allocated to the control group

Value

Total sample size (numeric)

References

Cundill, B., & Alexander, N. D. E. (2015). Sample size calculations for skewed distributions. BMC Medical Research Methodology, 15(1), 1–9. https://doi.org/10.1186/s12874-015-0023-0

skewsamp documentation built on Dec. 17, 2021, 1:07 a.m.