Orthogonalizing parametric link transformation families in binary regression analysis

DOI10.2307/3315574zbMath0761.62100OpenAlexW2168722776MaRDI QIDQ4016412

Claudia Czado, Thomas J. Santner

Publication date: 14 December 1992

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3315574

zbMATH Keywords

logistic regressionorthogonal reparametrizationlink functionsapproximate orthogonalityregression estimatesimproved numerical stabilitybinary regression analysislocally orthogonalorthogonalizing parametric link transformation families

Mathematics Subject Classification ID

Point estimation (62F10) Linear inference, regression (62J99)

Related Items

Bayesian inference of binary regression models with parametric link, Parametric link modification of both tails in binary regression, Norm restricted maximum likelihood estimators for binary regression models with parametric link, On selecting parametric link transformation families in generalized linear models, Choice of link and variance function for generalized linear mixed models: a case study with binomial response in proteomics, Bayesian ordinal and binary regression models with a parametric family of mixture links, The effect of link misspecification on binary regression inference

Cites Work

• The effect of link misspecification on binary regression inference
• Goodness of Link Tests for Generalized Linear Models
• On two families of transformations to additivity for binary response data
• The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis
• Discrimination among some parametric models
• A guide to the Burr type XII distributions
• Cumulative Frequency Functions