On the Hauck–Donner Effect in Wald Tests: Detection, Tipping Points, and Parameter Space Characterization

DOI10.1080/01621459.2021.1886936zbMath1515.62036arXiv2001.08431OpenAlexW3133198123WikidataQ113279330 ScholiaQ113279330MaRDI QIDQ6110699

Thomas W. Yee

Publication date: 6 July 2023

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2001.08431

zbMATH Keywords

regularity conditions\(p\)-valuesignificance testingiteratively reweighted least squares algorithmvector generalized linear model

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03) Approximations to statistical distributions (nonasymptotic) (62E17)

Cites Work

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• Vector generalized linear and additive models. With an implementation in R
• Modeling survival data: extending the Cox model
• High-dimensional inference: confidence intervals, \(p\)-values and R-software \texttt{hdi}
• p-Values for High-Dimensional Regression
• On the existence of maximum likelihood estimates in logistic regression models
• Maximum Likelihood Fitting of General Risk Models to Stratified Data
• The Danger of Extrapolating Asymptotic Local Power
• On the Use of Wald's Test in Exponential Families
• Wald's Test as Applied to Hypotheses in Logit Analysis
• Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information
• Improved Estimation in Cumulative Link Models
• The ASA Statement on p-Values: Context, Process, and Purpose

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