Results 241 to 250 of about 6,120,728 (295)

Profile monitoring for a binary response

IIE Transactions, 2009
Pertaining to industrial applications in which the response variable of interest is binary, this paper studies how the profile functional relationship between the response and predictor variables can be monitored using logistic regression. Under such a premise, several Hotelling T 2 charts that have been studied under continuous response variable to ...

exaly   +2 more sources

Reliability of binary analytical responses

TrAC - Trends in Analytical Chemistry, 2005
Abstract Binary response is clearly qualitative analytical information, which is become more and more important, as it is recognized as rapid information to solve solutions to a wide variety of problems. The metrology and the corresponding quality-assurance issues associated with this type of information are just being developed.
Helena Téllez Lozano, Ángel Ríos
exaly   +2 more sources

Testing for Independence of Binary Responses

Biometrical Journal, 1986
AbstractIn the context of experiments involving visual inspection of random dot patterns the problem of testing the null hypothesis of independence of binary responses is considered. A flexible model for dependence between binary responses is proposed. Two tests, optimal under different versions of the model, are derived.
FIDLER, [No Value], DEJONGE, AB
openaire   +2 more sources

Feedback Control for Binary Response

2017 Conference on Technologies and Applications of Artificial Intelligence (TAAI), 2017
Defect rate control is crucial in industries. When binary response is considered, the defect rate is the average of these binary responses. In this study, with logistic regression model and sparsity assumption, the feedback control problem is expressed as an optimization problem which solves a hinge loss with an L1 penalty. Here the hinge loss function
Ping-Yang Chen, Chi-Chun Hsia, Yen-Hao Su, Ray-Bing Chen, Sheng-Mao Chang   +4 more
openaire   +1 more source

Association Models for a Multivariate Binary Response

Biometrics, 2000
Summary.Models for a multivariate binary response are parameterized by univariate marginal proba‐bilities and dependence ratios of all orders. Thew‐order dependence ratio is the joint success probability ofwbinary responses divided by the joint success probability assuming independence. This parameterization supports likelihood‐based inference for both
Ekholm, Anders, McDonald, John W., Smith, Peter W.F.   +2 more
openaire   +3 more sources

Network and covariate adjusted response‐adaptive design for binary response

Statistics in Medicine, 2023
Randomization is a distinguishing feature of clinical trials for unbiased assessment of treatment efficacy. With a growing demand for more flexible and efficient randomization schemes and motivated by the idea of adaptive design, in this article we propose the network and covariate adjusted response‐adaptive (NCARA) design that can concurrently manage ...
Hao Mei, Jiaxin Xie, Yichen Qin, Yang Li
openaire   +3 more sources

Power of Tests in Binary Response Models [PDF]

Econometrica, 1999
Most hypotheses in binary response models are composite. The null hypothesis is usually that one or more slope coefficients are zero. Typically, the sequence of alternatives of interest is one in which the slope coefficients are increasing in absolute value.
Wurtz, Allan; id_orcid 0009-0007-0080-7284, Savin, Gene   +1 more
openaire   +1 more source

Response shrinkage estimators in binary regression

Computational Statistics & Data Analysis, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gerhard Tutz 0001, Florian Leitenstorfer
openaire   +1 more source