Assessing Local Influence in Measurement Error Models

Andy H. Lee, Yuejun Zhao

Research output: Contribution to journalComment/debate

Abstract

We consider the assessment of local influence for generalized linear models when the covariates are measured with errors. We show how to evaluate the effect that perturbations to the data, case weights, and model assumptions may have on the parameter estimates. Based on the likelihood displacement functions, some useful influence diagnostics are derived. Two examples illustrate application of the proposed diagnostics and assessment of the measurement error assumptions.
Original languageEnglish
Pages (from-to)829-841
Number of pages13
JournalBiometrical Journal
Volume38
Issue number7
DOIs
Publication statusPublished - 1996

Fingerprint

Dive into the research topics of 'Assessing Local Influence in Measurement Error Models'. Together they form a unique fingerprint.

Cite this