n_glm {skewsamp} | R Documentation |
Calculate sample size for a group comparison via generalized linear models
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 |
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: |
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