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This function performs Dunnett's test for comparing multiple treatment levels to a control using various model specifications, including options for random effects and variance structures.

Usage

dunnett_test(
  data,
  response_var = "Response",
  dose_var = "Dose",
  tank_var = "Tank",
  control_level = NULL,
  include_random_effect = TRUE,
  variance_structure = c("homoscedastic", "heteroscedastic"),
  alpha = 0.05,
  conf_level = 0.95,
  return_model = FALSE,
  alternative = c("two.sided", "greater", "less")
)

Arguments

data

A data frame containing the dose-response data

response_var

Name of the response variable column

dose_var

Name of the dose/treatment variable column

tank_var

Name of the blocking/tank variable column (optional)

control_level

The level of dose_var to use as control (default is minimum dose)

include_random_effect

Logical, whether to include random effects for blocks/tanks

variance_structure

Character, specifying the variance structure: "homoscedastic" (default) or "heteroscedastic"

alpha

Significance level for determining NOEC (default = 0.05)

conf_level

Confidence level for intervals (default = 0.95)

return_model

Logical, whether to return the fitted model object (default = FALSE)

alternative

a character string specifying the alternative hypothesis, must be one of '"two.sided"' (default), '"greater"' or '"less"'.

Value

A list containing the Dunnett test results, NOEC value, and optionally the model object