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Mixed-level designs with orthogonality and relatively optimal run order
Wenwen Hu1, Zujun Ou1, Qiao Peng1
1College of Mathematics and Statistics, Jishou University, Jishou, People's Republic of China.
Journal of Applied Statistics
|September 18, 2024
Summary
This study introduces new methods for designing experiments with mixed-level factors. These designs ensure orthogonality and optimize run order, minimizing experimental costs or enhancing robustness against time trends.
Area of Science:
- Statistics
- Experimental Design
Background:
- Orthogonality and run order optimality are key criteria in experimental design.
- Mixed-level designs are crucial for experiments with factors at unequal levels.
Purpose of the Study:
- To develop construction methods for mixed-level designs balancing orthogonality and run order optimality.
- To propose methods for obtaining orthogonal main-effect plans with minimized or maximized level changes.
Main Methods:
- Construction of mixed-level designs incorporating orthogonality and level change considerations.
- Application of the collapsing factor method to derive orthogonal main-effect plans.
Main Results:
- Novel construction methods for mixed-level designs are presented.
- Orthogonal main-effect plans with controlled level changes are successfully obtained.
Conclusions:
- The developed designs ensure cost-effectiveness or robustness to time trends in practical experiments.
- These methods provide valuable tools for efficient and reliable experimental planning.
Keywords:
62K0562K15Mixed-level orthogonal designNormalized Sylvester-Hadamard matrixlevel changeorthogonal main-effect planreplacement methodMore Related Videos
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