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Locally D-Optimal Designs for Binary Responses and Multiple Continuous Design Variables

Author

Listed:
  • Zhongshen Wang

    (Apellis Pharmaceuticals, Inc.)

  • John Stufken

    (University of North Carolina at Greensboro)

Abstract

We identify locally D-optimal designs for binary data when a generalized linear model with multiple continuous covariates whose values can be selected at the design stage. Yang et al. (Stat Sin 21:1415–1430, 2011) provided an explicit form for D-optimal designs when there are no interaction effects between the design variables. After providing an alternative proof of that result, we generalize the result by identifying D-optimal designs for models with interactions between the design variables that satisfy the strong effect heredity principle. We also employ orthogonal arrays to obtain more practical D-optimal designs with a smaller support size.

Suggested Citation

  • Zhongshen Wang & John Stufken, 2022. "Locally D-Optimal Designs for Binary Responses and Multiple Continuous Design Variables," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 101-113, September.
    • Handle: RePEc:spr:jqecon:v:20:y:2022:i:1:d:10.1007_s40953-022-00304-z
    DOI: 10.1007/s40953-022-00304-z
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    References listed on IDEAS

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    1. Kabera, M. Gaëtan & Haines, Linda M. & Ndlovu, Principal, 2012. "A note on the construction of locally D- and DS-optimal designs for the binary logistic model with several explanatory variables," Statistics & Probability Letters, Elsevier, vol. 82(5), pages 865-870.
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      Keywords

      Locally optimal design; D-optimality; Multiple covariates; Equivalence theorem; Orthogonal arrays;
      All these keywords.

      JEL classification:

      • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
      • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
      • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General

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