What question did this study set out to answer?

To develop and evaluate an optimal experimental design framework for dual-response systems that concurrently evaluate normal continuous and binomial binary response variables.

February 7, 2021Quality and Reliability Engineering International

Optimal designs for dual response systems for the normal and binomial case

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To develop and evaluate an optimal experimental design framework for dual-response systems that concurrently evaluate normal continuous and binomial binary response variables.
Formulated a weighted objective function combining the standard D-criterion for linear regression models and the Bayesian D-criterion for binomial logistic regression models.
Generated computer-optimal experimental designs across varying response weight combinations using a coordinate-exchange algorithm.
Investigated the design sensitivity and robustness relative to the prior distributions specified for the Bayesian logistic component.
Produced viable dual-response designs that flexibly balance estimation efficiency between linear and logistic model components depending on assigned criteria weights.
Demonstrated that design coordinate configurations and relative model efficiencies vary substantially according to the specified prior distributions and relative response weighting.

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Implication

Computational study demonstrates weighted optimal designs for dual continuous and binary responses, highlighting improved multi-objective experimental decision-making.

Cite This Study

Burke et al. (2021) studied this question.

synapsesocial.com/papers/6a9135805a27f97d0d65e3ff https://doi.org/10.1002/qre.2837

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Implication

Computational study demonstrates weighted optimal designs for dual continuous and binary responses, highlighting improved multi-objective experimental decision-making.

Optimal designs for dual response systems for the normal and binomial case

Key Points

Discussion

Implication

Cite This Study

Optimal designs for dual response systems for the normal and binomial case

Key Points

Discussion

Implication

Cite This Study

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