Explicit influence analysis in two-treatment balanced crossover models

Abstract

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.

Keywords

delta-beta influence; explicit maximum likelihood estimate; mixed linear model; multiple-period crossover design; perturbation scheme

Published in

Mathematical Methods of Statistics
2015, volume: 24, number: 1, pages: 16-36

SLU Authors

• von Rosen, Dietrich

  • Department of Energy and Technology, Swedish University of Agricultural Sciences
    
  • Linköping University

UKÄ Subject classification

Probability Theory and Statistics

Publication identifier

• DOI: https://doi.org/10.3103/S1066530715010020

Permanent link to this page (URI)

https://res.slu.se/id/publ/66438