Tony O'Hagan - Academic pages - Abstracts

## Estimating species sensitivity distributions with the aid of expert judgements

O'Hagan, A, Crane, M., Grist, E. P. M. and Whitehouse, P.

*Department of Probability and Statistics, University of Sheffield,
Sheffield, England*,
*Crane Consultants, Faringdon, Oxfordshire, England*,
*CSIRO Marine Research, Hobart, Tasmania, Australia* and
*Environment Agency, Wallingford, Oxfordshire, England*

**Publication details: **
Submitted to *Applied Statistics*.

### Abstract

A species sensitivity distribution (SSD) is the probability distribution of
some measure of toxicity to a certain chemical in a population of animal species.
Given data consisting of estimates of toxicity for a number of species present
in the habitat of interest, the SSD is typically estimated by assuming that
these values are a random sample from a lognormal distribution and estimating
the lognormal parameters. The principal deficiency of this approach is the assumption
that the data are from a random sample of species. In practice, the species
for which data are available are determined in non-random ways and are likely
to be highly non-representative of the population.

We present a method of inference
about SSDs that draws on expert judgement about which species are likely to
be more sensitive to the chosen chemical. The expert judgements allow us to take
some account of non-representativeness of the available data.
We adopt a hierarchical random-effects model which recognises that species
within the same family are likely to have similar sensitivities,
and employ a Bayesian approach to analysis that allows direct inference
about quantiles of the SSD.

*Keywords*: Bayesian inference; censored data; chlorpyrifos; environmental standards; HC5; hierarchical model; LC50; SSD; toxicology.

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Updated: 11 May 2005
Maintained by: Tony O'Hagan