Dunnett.GLM: Dunnett.GLM

In qountstat: Statistical Analysis of Count Data and Quantal Data

Dunnett.GLM

Description

When conducting statistical tests with multiple treatments, such as a control group and increasing concentrations of a test substance, ANOVA and parametric post-hoc tests (e.g. Dunnett's test) are commonly used. However, these tests require the assumptions of homogeneous variances and normally distributed data. For count data (e.g. counts of animals), these assumptions are typically violated, as the data are usually Poisson-distributed. The Dunnett.GLM function is based on a GLM followed by a Dunnett test to the model estimates. It was implemented to serve as an alternative approach to CPCAT while using a Quasi-Poisson regression. The basic approach from Hothorn and Kluxen (2020) was adjusted to overcome methodological issues (see description of 'zero.treatment.action parameter'). For details on the structure of the input data, please refer to the dataset 'Daphnia.counts' provided alongside this package.

Usage

Dunnett.GLM(
  groups,
  counts,
  control.name = NULL,
  zero.treatment.action = "identity.link",
  show.output = TRUE
)

Arguments

groups	Group vector
counts	Vector with count data
control.name	Character string with control group name (optional)
zero.treatment.action	Method for dealing with treatments only containing zeros (use either "identity.link" or "log(x+1)"). The method is only used if the data set contains dose/concentration groups that exclusively contain zero values (since the basic method provides for a logarithmic transformation of the data averages, it would lead to incorrect results). To deal with this methodological shortcoming, two options were implemented. The 'identity.link' option: the 'identity' link is used in the GLM instead of the 'log' link, i.e. the data are no longer transformed. The 'log(x+1)' option: The 'log' link is retained and 1 is added to each count value at the start of the procedure so that the subsequent log-transformation can be carried out without any problems. Note that both options may slightly distort the results.
show.output	Show/hide output

Value

R object with results and information from Dunnett.GLM calculations

References

Hothorn, L.; Kluxen, F. (2020): Statistical analysis of no observed effect concentrations or levels in eco-toxicological assays with overdispersed count endpoints. In: bioRxiv, 2020, https://doi.org/10.1101/2020.01.15.907881

Examples

Daphnia.counts	# example data provided alongside the package

# Test Dunnett.GLM with 'identity.link' option
Dunnett.GLM(groups = Daphnia.counts$Concentration,
			   counts = Daphnia.counts$Number_Young,
			   control.name = NULL,
			   zero.treatment.action = "identity.link",
			   show.output = TRUE)

# Test Dunnett.GLM with 'log(x+1)' option
Dunnett.GLM(groups = Daphnia.counts$Concentration,
		   counts = Daphnia.counts$Number_Young,
		   control.name = NULL,
		   zero.treatment.action = "log(x+1)",
		   show.output = TRUE)

qountstat documentation built on April 4, 2025, 12:18 a.m.