2007
DOI: 10.1111/j.1467-9876.2007.00588.x
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Statistical Inference for Olfactometer Data

Abstract: Olfactometer experiments are used to determine the effect of odours on the behaviour of organisms such as insects or nematodes, and typically result in data comprising many groups of small overdispersed counts. We develop a non-homogeneous Markov chain model for data from olfactometer experiments with parasitoid wasps and discuss a relation with the Dirichlet-multinomial distribution. We consider the asymptotic relative efficiencies of three different observation schemes and give an analysis of data intended t… Show more

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Cited by 18 publications
(20 citation statements)
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References 15 publications
(14 reference statements)
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“…The entity computing a repetition in the statistical analysis corresponds to the response of a group of nematodes released, which was shown to follow a multinomial distribution (50). Because the data did not conform to simple variance assumptions implied in using the multinomial distribution, we used quasi-likelihood functions to compensate for the overdispersion of nematodes within the olfactometer (51).…”
Section: E␤c Emission Screensmentioning
confidence: 99%
“…The entity computing a repetition in the statistical analysis corresponds to the response of a group of nematodes released, which was shown to follow a multinomial distribution (50). Because the data did not conform to simple variance assumptions implied in using the multinomial distribution, we used quasi-likelihood functions to compensate for the overdispersion of nematodes within the olfactometer (51).…”
Section: E␤c Emission Screensmentioning
confidence: 99%
“…The adequacy of the model was assessed through likelihood ratio statistics and examination of residuals in the software package R (R Foundation of Statistical Software, version 2.4.0; www. r-project.org) Ricard and Davison, 2007). We tested treatment effects (i.e., odor sources) for naive and experienced wasps individually.…”
Section: Bioassaysmentioning
confidence: 99%
“…We also took into account the significant overdispersion of the data previously observed (Davison 2003;Tamò et al 2006) by using a stochastic version of the model. Our model also considered the censored nature of our data since not all the wasps made a choice during the 30 min (Ricard and Davison 2007).…”
Section: Statisticsmentioning
confidence: 99%