On generalized multinomial models and joint percentile estimation

DOI10.1016/j.jspi.2013.08.015zbMath1279.62069arXiv1211.6915OpenAlexW2963913913MaRDI QIDQ393556

Mohammad Hasan, H. S. Yoon

Publication date: 23 January 2014

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

Full work available at URL: https://arxiv.org/abs/1211.6915

zbMATH Keywords

confidence regionsstandardizationmulticategorical logistic linkparameter orthogonality

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Point estimation (62F10)

Related Items

Robust designs for multinomial models

Uses Software

• Fahrmeir
• MCS
• bootlib

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Kernel-based semiparametric multinomial logit modelling of political party preferences
• Choosing the link function and accounting for link uncertainty in generalized linear models using Bayes factors
• Robust designs for misspecified logistic models
• Robust designs for generalized linear models with possible overdispersion and misspecified link functions
• Optimization in a multivariate generalized linear model situation
• The effect of link misspecification on binary regression inference
• Global optimization by multilevel coordinate search
• On selecting parametric link transformation families in generalized linear models
• Regression analysis under link violation
• Bayesian ordinal and binary regression models with a parametric family of mixture links
• Comparison of designs for generalized linear models under model misspecification
• Dose-Finding Designs for HIV Studies
• An Asymptotic Confidence Region for the ED 100p from the Logistic Response Surface for a Combination of Agents
• Goodness-of-link testing in ordinal regression models
• Goodness of Link Tests for Generalized Linear Models
• On two families of transformations to additivity for binary response data
• Discrimination among some parametric models
• Norm restricted maximum likelihood estimators for binary regression models with parametric link
• Robustness of Design in Dose–Response Studies
• A Strategy for Dose-Finding and Safety Monitoring Based on Efficacy and Adverse Outcomes in Phase I/II Clinical Trials
• Interval Estimation of the Median Lethal Dose
• Some robust design strategies for percentile estimation in binary response models
• Linear Statistical Inference and its Applications
• Multivariate statistical modelling based on generalized linear models.
• Interval estimation of the \(ED_{50}\) when a logistic dose-response curve is incorrectly assumed