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Influence diagnostics for count data under AB–BA crossover trials
Stockholm University, Faculty of Social Sciences, Department of Statistics. Department of Automation, Shanghai Jiao Tong University, Shanghai, China.
Stockholm University, Faculty of Social Sciences, Department of Statistics.ORCID iD: 0000-0002-8610-0365
2015 (English)In: Statistical Methods in Medical Research, ISSN 0962-2802, E-ISSN 1477-0334Article in journal (Refereed) Accepted
Abstract [en]

This paper aims to develop diagnostic measures to assess the influence of data perturbations on estimates in ABBA 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 allows 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
2015.
Keyword [en]
Generalised mixed linear model, Influential observation, Model diagnostics, Perturbation scheme, Poisson model
National Category
Probability Theory and Statistics
Research subject
Statistics; Mathematical Statistics
Identifiers
URN: urn:nbn:se:su:diva-121740OAI: oai:DiVA.org:su-121740DiVA: diva2:861007
Funder
The Royal Swedish Academy of Sciences, FOA12H-204The Royal Swedish Academy of Sciences, FOA12Magn-111Swedish Research Council, 2010-18915-75688-45
Available from: 2015-10-14 Created: 2015-10-14 Last updated: 2017-12-01Bibliographically approved

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