Bayesian design of experiment for quantal responses: What is promised versus what is delivered
type: Item
instance of: scholarly article
title: Bayesian design of experiment for quantal responses: What is promised versus what is delivered
zbMATH Open document ID: 0877.62073
DOI: 10.1016/0378-3758(95)00120-4
author: Dongchu Sun
author: Robert K. Tsutakawa
author: Wang-Shu Lu
published in: Journal of Statistical Planning and Inference
publication date: 1997-12-14T00:00:00Z
Mathematics Subject Classification ID: 62K05
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 906696
zbMATH Keywords: logistic distribution
zbMATH Keywords: LD50
zbMATH Keywords: posterior variance
zbMATH Keywords: Monte Carlo integration
MaRDI profile type: Publication
full work available at URL: 0378-3758(95)00120-4
OpenAlex ID: W2048374674
cites work: Experimental Design for Binary Data
cites work: Optimum Experimental Designs for Properties of a Compartmental Model
cites work: Optimal Bayesian design applied to logistic regression experiments
cites work: Q4181158
cites work: Q3672893
cites work: Extended Models for Quantal Response Data
cites work: Design of Experiment for Bioassay
cites work: Selection of Dose Levels for Estimating a Percentage Point of a Logistic Quantal Response Curve
description: scientific article; zbMATH DE number 906696