Quantile dispersion graphs for evaluating and comparing designs for logistic regression models
From MaRDI portal
Publication:951906
DOI10.1016/S0167-9473(02)00182-2zbMath1375.62012OpenAlexW2078817951MaRDI QIDQ951906
Kevin S. Robinson, André I. Khuri
Publication date: 4 November 2008
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0167-9473(02)00182-2
generalized linear modelsbinary responseresponse surface methodologyprediction biasdesign dependence on unknown parametersscaled mean-squared error of prediction
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Cites Work
- Optimal Bayesian design applied to logistic regression experiments
- A graphical approach for evaluating and comparing designs for nonlinear models.
- Bayesian design for accelerated life testing
- Bayesian D-optimal designs for the exponential growth model
- Bayesian experimental design: A review
- Bias correction for exponential family nonlinear modles
- An Asymptotic Confidence Region for the ED 100p from the Logistic Response Surface for a Combination of Agents
- Bias in nonlinear regression
- Robust Procedures for Drug Combination Problems with Quantal Responses
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