qountstat - Statistical Analysis of Count Data and Quantal Data
Methods for statistical analysis of count data and quantal
data. For the analysis of count data an implementation of the
Closure Principle Computational Approach Test ("CPCAT") is
provided (Lehmann, R et al. (2016)
<doi:10.1007/s00477-015-1079-4>), as well as an implementation
of a "Dunnett GLM" approach using either a Quasi-Poisson, a
negative binomial or a Poisson regression (Hothorn, L, Kluxen,
F (2020) <doi:10.1101/2020.01.15.907881>). For the analysis of
quantal data an implementation of the Closure Principle
Fisher–Freeman–Halton test ("CPFISH") is provided (Lehmann, R
et al. (2018) <doi:10.1007/s00477-017-1392-1>). P-values and
no/lowest observed (adverse) effect concentration values are
calculated. All implemented methods include further functions
to evaluate the power and the minimum detectable difference
using a bootstrapping approach. A model-agnostic,
simulation-calibrated diagnostic for overdispersion in grouped
count data is provided to support the choice between the
implemented methods.
