Wadley’s problem frequently emerges in dosage-mortality data and is one in which
the number of surviving organisms is observed but the number initially treated is
unknown. Data in this setting are also often overdispersed, that is the variability
within the data exceeds that described by the distribution modelling it. The aim of
this thesis is to explore distributions that can accommodate overdispersion in a
Wadley’s problem setting. Two methods are essentially considered. The first
considers adapting the beta-binomial and multiplicative binomial models that are
frequently used for overdispersed binomial-type data to a Wadley’s problem setting.
The second strategy entails modelling Wadley’s problem with a distribution that is
suitable for modelling overdispersed count data. Some of the distributions introduced
can be used for modelling overdispersed count data as well as overdispersed doseresponse
data from a Wadley context. These models are compared using goodness of
fit tests, deviance and Akaike’s Information Criterion and their properties are
explored. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2009.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ukzn/oai:http://researchspace.ukzn.ac.za:10413/9319 |
| Date | January 2009 |
| Creators | Leask, Kerry Leigh. |
| Contributors | Haines, Linda M., Matthews, Glenda B. |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | English |
| Type | Thesis |
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