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.
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[cre, aut],
Christian Dietrich [aut],
Thomas Graeff [aut],
Magnus Wang [aut]