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Influence diagnostics for count data under AB-BA crossover trials
Stockholm University, Faculty of Social Sciences, Department of Statistics.
Stockholm University, Faculty of Social Sciences, Department of Statistics.
Number of Authors: 32017 (English)In: Statistical Methods in Medical Research, ISSN 0962-2802, E-ISSN 1477-0334, Vol. 26, no 6, p. 2938-2950Article in journal (Refereed) Published
Abstract [en]

This paper aims to develop diagnostic measures to assess the influence of data perturbations on estimates in AB-BA crossover studies with a Poisson distributed response. Generalised mixed linear models with normally distributed random effects are utilised. We show that in this special case, the model can be decomposed into two independent sub-models which allow to derive closed-form expressions to evaluate the changes in the maximum likelihood estimates under several perturbation schemes. The performance of the new influence measures is illustrated by simulation studies and the analysis of a real dataset.

Place, publisher, year, edition, pages
2017. Vol. 26, no 6, p. 2938-2950
Keywords [en]
Generalised mixed linear model, Influential observation, model diagnostics, perturbation scheme, Poisson model
National Category
Probability Theory and Statistics Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:su:diva-151145DOI: 10.1177/0962280215615597ISI: 000418307900030PubMedID: 26596351OAI: oai:DiVA.org:su-151145DiVA, id: diva2:1173023
Available from: 2018-01-11 Created: 2018-01-11 Last updated: 2018-01-11Bibliographically approved

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