Collinearity in generalized linear regression

DOI10.1080/03610929308831126zbMath0785.62076OpenAlexW2086982132MaRDI QIDQ4275726

Brian D. Marx, Emmanuel Lesaffre

Publication date: 20 January 1994

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929308831126

zbMATH Keywords

maximum likelihood estimatorlogistic regressioncollinearityexplanatory variablesbiased estimationcondition indexill- conditioning\(ML\)-collinearityexistence of \(ML\) estimatesweighted variables

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) Diagnostics, and linear inference and regression (62J20)

Related Items (10)

Accounting for endogeneity in regression models using copulas: a step-by-step guide for empirical studies ⋮ Logistic regression diagnostics in ridge regression ⋮ The red indicator and corrected VIFs in generalized linear models ⋮ Influence diagnostics in gamma ridge regression model ⋮ A new multicollinearity diagnostic for generalized linear models ⋮ Profile monitoring for count data using Poisson and Conway-Maxwell-Poisson regression-based control charts under multicollinearity problem ⋮ A new biased estimator in logistic regression model ⋮ Liu-Type Negative Binomial Regression: A Comparison of Recent Estimators and Applications ⋮ Performance of some ridge estimators for the gamma regression model ⋮ On linearized ridge logistic estimator in the presence of multicollinearity

Uses Software

• GLIM

Cites Work

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• The general problem of ill conditioning and its role in statistical analysis
• Principal component estimation for generalized linear regression
• On the existence of maximum likelihood estimates in logistic regression models
• On the small sample properties of norm-restricted maximum likelihood estimators for logistic regression models
• Collinearity in generalized linear models
• On the Use of Wald's Test in Exponential Families
• Alternative estimators in logistic regression when the data are collinear
• A note on A. Albert and J. A. Anderson's conditions for the existence of maximum likelihood estimates in logistic regression models
• Multiple group logistic discrimination
• Wald's Test as Applied to Hypotheses in Logit Analysis

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