Estimating logistic regression models when the dependent variable has no variance

DOI10.1080/03610929208830787zbMath0800.62366OpenAlexW1971478165MaRDI QIDQ3135590

Dan Steinberg, Nicholas Scott Cardell

Publication date: 11 October 1993

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

Full work available at URL: https://doi.org/10.1080/03610929208830787

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Point estimation (62F10) Linear inference, regression (62J99)

Related Items (5)

Modeling qualitative outcomes by supplementing participant data with general population data: a new and more versatile approach ⋮ Case-control studies with contaminated controls ⋮ Estimating the class prior for positive and unlabelled data via logistic regression ⋮ Learning from positive and unlabeled data: a survey ⋮ A Class of Pseudolikelihood Ratio Tests for Homogeneity in Exponential Tilt Mixture Models

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• Maximum score estimation of the stochastic utility model of choice
• Maximum Likelihood Estimator for Choice-Based Samples
• The Estimation of Choice Probabilities from Choice Based Samples
• Sample Selection Bias as a Specification Error

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