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Explicit Influence Analysis in Two-Treatment Balanced Crossover Models
Stockholm University, Faculty of Social Sciences, Department of Statistics.
Stockholm University, Faculty of Social Sciences, Department of Statistics.
2015 (English)In: Mathematical Methods of Statistics, ISSN 1066-5307, E-ISSN 1934-8045, Vol. 24, no 1, 16-36 p.Article in journal (Refereed) Published
Abstract [en]

This paper considers how to detect influential observations in crossover models with random individual effects. Two influence measures, the delta-beta influence and variance-ratio influence, are utilized as tools to evaluate the influence of the model on the estimates of mean and variance parameters with respect to case-weighted perturbations, which are introduced to the model for studying the ‘influence’ of cases. The paper provides explicit expressions of the delta-beta and variance-ratio influences for the general two-treatment balanced crossover models when the proposed decompositions for the perturbed models hold. The influence measures for each parameter turn out to be closed-form functions of orthogonal projections of specific residuals in the unperturbed model.

Place, publisher, year, edition, pages
2015. Vol. 24, no 1, 16-36 p.
Keyword [en]
delta-beta influence, explicit maximum likelihood estimate, mixed linear model, multiple-period crossover design, perturbation scheme.
National Category
Probability Theory and Statistics
Research subject
Statistics; Mathematical Statistics
Identifiers
URN: urn:nbn:se:su:diva-115136DOI: 10.3103/S1066530715010020OAI: oai:DiVA.org:su-115136DiVA: diva2:795767
Funder
The Royal Swedish Academy of Sciences, FOA12H-204Swedish Research Council, 2010-18915-75688-45
Available from: 2015-03-17 Created: 2015-03-17 Last updated: 2017-12-04Bibliographically approved

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