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Influence diagnostics for count data under AB-BA crossover trials
Stockholm University, Sweden.
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering. Swedish University of Agriculture Science, Sweden.
Stockholm University, Sweden.
2017 (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
SAGE PUBLICATIONS LTD , 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
Identifiers
URN: urn:nbn:se:liu:diva-144157DOI: 10.1177/0962280215615597ISI: 000418307900030PubMedID: 26596351OAI: oai:DiVA.org:liu-144157DiVA, id: diva2:1171792
Note

Funding Agencies|Stockholm University; Royal Swedish Academy of Sciences [FOA12H-204, FOA12Magn-111]; Swedish Research Council [2010-18915-75688-45]; Estonian Science Foundation [ETF8294]

Available from: 2018-01-08 Created: 2018-01-08 Last updated: 2018-01-08

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CiteExportLink to record
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  • de-DE
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  • nn-NB
  • sv-SE
  • Other locale
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Output format
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