Optimal designs for mixed continuous and binary responses with quantitative and qualitative factors

DOI10.1016/j.jmva.2020.104712zbMath1462.62482OpenAlexW3113242532MaRDI QIDQ2222236

Ming-Hung Kao, Hazar Khogeer

Publication date: 26 January 2021

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2020.104712

zbMATH Keywords

sequential quadratic programmingChebyshev systemoptimality criteriaapproximate designcomplete class

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Optimal statistical designs (62K05) Generalized linear models (logistic models) (62J12) Quadratic programming (90C20)

Related Items (1)

A generative approach to modeling data with quantitative and qualitative responses

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• D-optimal designs for multiresponse linear models with a qualitative factor
• Algorithmic construction of optimal designs on compact sets for concave and differentiable criteria
• A note on the de la Garza phenomenon for locally optimal designs
• Identifying locally optimal designs for nonlinear models: A simple extension with profound consequences
• On linear regression designs which maximize information
• General equivalence theory for optimum designs (approximate theory)
• D-optimal designs for a multivariate regression model
• Optimal designs for dose response curves with common parameters
• Locally optimal designs for mixed binary and continuous responses
• Complete class results for the moment matrices of designs over permutation-invariant sets
• Optimum designs for multi-factor models
• Optimum designs for a multiresponse regression model
• A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs
• Saturated locally optimal designs under differentiable optimality criteria
• Locally  p-optimal designs for generalized linear models with a single-variable quadratic polynomial predictor
• Analysis of Mixed Data
• Designing dose-finding studies with an active control for exponential families
• Response models for mixed binary and quantitative variables
• Optimal Group Testing Designs for Estimating Prevalence with Uncertain Testing Errors
• Regression Models for a Bivariate Discrete and Continuous Outcome with Clustering
• Locally optimal designs for binary dose‐response models
• Optimal designs for active controlled dose-finding trials with efficacy-toxicity outcomes
• Locally Optimal Designs for Estimating Parameters

This page was built for publication: Optimal designs for mixed continuous and binary responses with quantitative and qualitative factors