View source: R/DunnettGLMPower.R
| Dunnett.GLM.power | R Documentation | 
The basic idea of Dunnett.GLM power calculations is to do parametric bootstrapping for each dose/concentration group and to evaluate the proportion of results significantly different from the control.
Dunnett.GLM.power(
  groups,
  counts,
  control.name = NULL,
  alpha = 0.05,
  bootstrap.runs = 200,
  use.fixed.random.seed = NULL,
  Dunnett.GLM.zero.treatment.action = "log(x+1)",
  show.progress = TRUE,
  show.results = TRUE
)
groups | 
 Group vector  | 
counts | 
 Vector with count data  | 
control.name | 
 Character string with control group name (optional)  | 
alpha | 
 Significance level  | 
bootstrap.runs | 
 Number of bootstrap runs  | 
use.fixed.random.seed | 
 Use fixed seed, e.g. 123, for reproducible results. If NULL no seed is set.  | 
Dunnett.GLM.zero.treatment.action | 
 GLM.Dunnett method to be used for treatments only containing zeros  | 
show.progress | 
 Show progress for each shift of lambda  | 
show.results | 
 Show results  | 
Data frame with results from power analysis
Daphnia.counts	# example data provided alongside the package
# Test Dunnett.GLM power
Dunnett.GLM.power(groups = Daphnia.counts$Concentration,
	counts = Daphnia.counts$Number_Young,
	control.name = NULL,
	alpha = 0.05,
	bootstrap.runs = 10,	# Caution: low number of bootstrap runs for testing
	use.fixed.random.seed = 123,  #fixed seed for reproducible results
	Dunnett.GLM.zero.treatment.action = "log(x+1)",
	show.progress = TRUE,
	show.results = TRUE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.