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Random Effects Ordinal Time Models for Grouped Toxicological Data from a Biological Control Assay

  • Marie-José Martinez
  • John P. Hinde
Chapter
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

Discrete survival times can be viewed as ordered multicategorical data. Here a continuation-ratio model is considered, which is particularly appropriate when the ordered categories represent a progression through different stages, such as survival through various times. This particular model has the advantage of being a simple decomposition of a multinomial distribution into a succession of hierarchical binomial models. In a clustered data context, random effects are incorporated into the linear predictor of the model to account for uncontrolled experimental variation. Assuming a normal distribution for the random effects, an EM algorithm with adaptive Gaussian quadrature is used to estimate the model parameters. This approach is applied to the analysis of grouped toxicological data obtained from a biological control assay. In this assay, different isolates of the fungus Beauveria bassiana were used as a microbial control for the Heterotermes tenuis termite, which causes considerable damage to sugarcane fields in Brazil. The aim is to study the pathogenicity and the virulence of the fungus in order to determine effective isolates for the control of this pest population.

Keywords

Adaptive quadrature Clustered data Multicategorical data Ordinal regression Random effects 

Notes

Acknowledgements

This work was part-funded under Science Foundation Ireland’s Research Frontiers Programme (07/RFP-MATF448) and Science Foundation Ireland’s BIO-SI project, grant number 07/MI/012.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Team MISTIS, INRIA Rhône-Alpes & Laboratoire Jean KuntzmannSaint-Ismier CedexFrance
  2. 2.School of Mathematics, Statistics and Applied MathematicsNational University of Ireland, GalwayGalwayIreland

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