qountstat

Statistical analysis of count data and quantal data in ecotoxicology.

The package determines no/lowest observed (adverse) effect concentrations (NOEC/LOEC) from the data of laboratory and field biotests and provides diagnostics for choosing an appropriate method.

Methods

Function	Purpose
CPCAT()	Closure Principle Computational Approach Test for count data
Dunnett.GLM()	Dunnett contrasts on a GLM, with a quasi-Poisson, negative binomial or Poisson distribution
CPFISH()	Closure Principle Fisher-Freeman-Halton test for quantal data
Overdispersion.test()	Simulation-calibrated diagnostic for overdispersion

Each method is accompanied by functions for the statistical power and for the bootstrapped minimum detectable difference, for example CPCAT.power() and CPCAT.bMDD().

Installation

From CRAN:

install.packages("qountstat")

The development version from GitHub:

# install.packages("remotes")
# remotes::install_github("BenniDaniels/qountstat")
install.packages("qountstat", repos = c('https://bennidaniels.r-universe.dev', 'https://cloud.r-project.org'))

Example

library(qountstat)

# Check whether the counts are compatible with a Poisson distribution
Overdispersion.test(groups = Daphnia.counts$Concentration,
                    counts = Daphnia.counts$Number_Young)

# Determine the NOEC with the CPCAT
CPCAT(groups = Daphnia.counts$Concentration,
      counts  = Daphnia.counts$Number_Young,
      use.fixed.random.seed = 123)

Citation

citation("qountstat")

References

Lehmann, R.; Bachmann, J.; Maletzki, D.; Polleichtner, C.; Ratte, H.; Ratte, M. (2016): A new approach to overcome shortcomings with multiple testing of reproduction data in ecotoxicology. Stochastic Environmental Research and Risk Assessment 30(3), 871-882. https://doi.org/10.1007/s00477-015-1079-4

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

Daniels, B.; Kotschik, P.; Walter-Rohde, S.; Graeff, T. (2026): When Counts Deviate: Robust Overdispersion Diagnostics for Ecotoxicity Data. Poster, 36th SETAC Europe Annual Meeting, Maastricht.

License

MIT, see LICENSE.