Case deletion diagnostics in multilevel models

Authors:
Lei Shi;Gemai Chen
Affiliations:
College of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, Yunnan 650221, PR China;Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, T2N 1N4, Canada and Department of Applied Mathematics, Southwest Jiaotong University, Chengdu, Sichuan, PR China
Venue:
Journal of Multivariate Analysis
Year:
2008

Citing 3
Cited 3

Sensitivity analysis in linear regression

Sensitivity analysis in linear regression
Case-deletion diagnostics for mixed models

Technometrics
Local influence in multilevel regression for growth curves

Journal of Multivariate Analysis

Influence diagnostics in nonlinear mixed-effects elliptical models

Computational Statistics & Data Analysis
Stepwise local influence analysis

Computational Statistics & Data Analysis
Deletion, replacement and mean-shift for diagnostics in linear mixed models

Computational Statistics & Data Analysis

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Abstract

This paper studies case deletion diagnostics for multilevel models. Using subset deletion, diagnostic measures for identifying influential units at any level are developed for both fixed and random parameters. Two approximate update formulae are derived. The first formula uses one-step approximation, while the second formula also includes the impact of estimating the random parameter. Two examples are used to illustrate the methodology developed.