Abstract
When fitting dose-response models to entomological data it is often necessary to take account of natural mortality and/or overdispersion. The standard approach to handle natural mortality is to use Abbott's formula, which allows for a constant underlying mortality rate. Commonly used overdispersion models include the beta-binomial model, logistic-normal, and discrete mixtures. Here we extend the standard natural mortality model by including a random effect to account for overdispersion. Parameter estimation is based on a combined EM Newton-Raphson algorithm, which provides a simple framework for maximum likelihood estimation of the natural mortality model. We consider the application of this model to data from an experiment on the use of a virus (PhopGV) for the biological control of worm larvae (Phthorimaea operculella) in potatoes. For this natural mortality model with a random effect we introduce the likelihood ratio test, effective dose, and the use of a simulated residual envelope for model checking. Comparisons are made with an equivalent beta-binomial model. The procedures are implemented in the R system.
| Original language | English |
|---|---|
| Pages (from-to) | 594-610 |
| Number of pages | 17 |
| Journal | Journal of Agricultural, Biological, and Environmental Statistics |
| Volume | 18 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Dec 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
Keywords
- Beta-binomial model
- Binomial model
- Bioassay
- EM algorithm
- Natural mortality
- Random effect
- Simulated envelope
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