Two-Level Multifactor Experiment Designs for Detecting the Presence of Interactions

Abstract

A design optimality criterion tr(L) - optimality is applied to the problem of designing two-level multifactor experiments to detect the presence of interactions among the controlled variables. Rules are given for constructing tr(L) - optimal foldover designs and tr(L) - optimal fractional factorial designs. Some results are given on the power of these designs for testing the hypothesis that there are no two-factor interactions. Modifications of the tr(L) - optimal designs to satisfy other experimental objectives (estimability of effects, detection of the presence of other nonlinear effects, estimation of the error variance) are suggested. Examples are given to demonstrate the application of these designs to (i) screening for interactions, and (ii) evaluating the first-order assumption in the sensitivity analysis of a computer code.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1980
Accession Number
ADA093573

Entities

People

  • Max D. Morris
  • Toby J. Mitchell

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Combinatorial Analysis
  • Computer Science
  • Computers
  • Data Science
  • Experimental Design
  • Factorial Design
  • Heat Flux
  • Information Science
  • Mathematics
  • Normal Distribution
  • Probability
  • Sensitivity
  • Statistics
  • United States
  • Universities
  • Wisconsin

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Regression Analysis.
  • Software Engineering.