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Dose Response Models with Natural Mortality and Random Effects

  • M. R. Urbano
  • , J. Hinde
  • , C. G.B. Demétrio
  • Londrina State University
  • University of São Paulo

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

2 Citations (Scopus)

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 languageEnglish
Pages (from-to)594-610
Number of pages17
JournalJournal of Agricultural, Biological, and Environmental Statistics
Volume18
Issue number4
DOIs
Publication statusPublished - Dec 2013

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger

Keywords

  • Beta-binomial model
  • Binomial model
  • Bioassay
  • EM algorithm
  • Natural mortality
  • Random effect
  • Simulated envelope

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