A characteristic function approach to the biased sampling model, with application to robust logistic regression

DOI10.1016/j.jspi.2007.01.004zbMath1133.62020OpenAlexW1965637354MaRDI QIDQ2475754

Howard D. Bondell

Publication date: 11 March 2008

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2007.01.004

zbMATH Keywords

logistic regressionrobust regressionminimum distancebiased sampling problemcase-control data

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric estimation (62G05) Generalized linear models (logistic models) (62J12) Sampling theory, sample surveys (62D05) Characteristic functions; other transforms (60E10)

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Robust estimation for ordinal regression ⋮ Robust instance-dependent cost-sensitive classification ⋮ A Wald-type test statistic based on robust modified median estimator in logistic regression models ⋮ Robust Inference and Modeling of Mean and Dispersion for Generalized Linear Models ⋮ Robust testing in the logistic regression model ⋮ Robust Wald-type methods for testing equality between two populations regression parameters: a comparative study under the logistic model ⋮ Robust semiparametric inference for polytomous logistic regression with complex survey design ⋮ Penalized robust estimators in sparse logistic regression ⋮ On the consistence of the modified median estimator for the logistic regression model

Uses Software

• nlmdl

Cites Work

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