Abstract
Entomological data are often overdispersed, characterised by a larger variance than assumed by simple standard models. It is important to model overdispersion properly in order to avoid incorrect and misleading inferences. Outcomes of interest are often in the form of counts or proportions and we present extended models that incorporate overdispersion, methods to assess its impact and model goodness-of-fit, and techniques to test treatment differences in the presence of overdispersion.
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Notes
- 1.
A Bernoulli trial is a random experiment with exactly two possible outcomes, “success” and “failure”, in which the probability of success is the same every time the experiment is conducted.
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Demétrio, C.G.B., Hinde, J., Moral, R.A. (2014). Models for Overdispersed Data in Entomology. In: Ferreira, C., Godoy, W. (eds) Ecological Modelling Applied to Entomology. Entomology in Focus, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-06877-0_9
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