64th ISI World Statistics Congress - Ottawa, Canada

64th ISI World Statistics Congress - Ottawa, Canada

Design and Analysis of Order-of-Addition Experiments

Organiser

FP
Frederick Kin Hing Phoa

Participants

  • FP
    Mr Frederick Kin Hing Phoa
    (Chair)

  • DL
    Prof. Dennis Lin
    (Presenter/Speaker)
  • Design of Experiments for Digital Twins

  • HX
    Prof. Hongquan Xu
    (Presenter/Speaker)
  • Designs for Order-of-Addition Screening Experiments

  • JH
    DRS Jing-Wen Huang
    (Presenter/Speaker)
  • A Systematic Design Construction and Analysis for Cost-Efficient Order-of-Addition Experiments

  • RM
    Dr Robert Mee
    (Presenter/Speaker)
  • Synthesis of Order-of-Addition Models

  • Category: International Statistical Institute

    Abstract

    Traditionally, factorial design is one of the most commonly used classes of experimental plans in scientific researches and induastrial processes. A hidden assumption behind these factorial designs is that the effect on the order of factor inputs is generally negligible, but it may not be true for all real-world scenarios, like the drug intakes in clinical trials. In order to incorporate order effects in experimental analyses, the order-of-addition (OofA) experiments has recently resurfaced among researchers in the design and analysis of experiments. This class of experiments aims to investigate how the different orders of factor inputs (e.g. medicine intakes) provide significant effects towards the response value, so that one can obtain the optimal order of factor inputs. This order-matter concept is useful not only in clinical trials but also in biochemistry, culinary, cosmetic industry, agriculture, and many industrial processes. The optimization of these factorial order effects leads to the best possible use of experimental resources. In this session, we gather leading experts to discuss the recent advances in the research of OofA experimental designs. Each of them introduce their own advancement to the design and analysis of OofA experiment in their presentation, so audiences can learn the design construction, design analysis, and its implementation to specific scientific problems of audiences' interests.