Regularities in data from factorial experiments

doi:10.1002/cplx.20123

Regularities in data from factorial experiments

2006-06-16

0

PRE

AI

DOI：10.1002/cplx.20123

原文链接

原文求助

摘要

En 中文

AbstractThis article documents a meta‐analysis of 113 data sets from published factorial experiments. The study quantifies regularities observed among factor effects and multifactor interactions. Such regularities are known to be critical to efficient planning and analysis of experiments and to robust design of engineering systems. Three previously observed properties are analyzed: effect sparsity, hierarchy, and heredity. A new regularity is introduced and shown to be statistically significant. It is shown that a preponderance of active two‐factor interaction effects are synergistic, meaning that when main effects are used to increase the system response, the interaction provides an additional increase and that when main effects are used to decrease the response, the interactions generally counteract the main effects. © 2006 Wiley Periodicals, Inc. Complexity 11: 32–45, 2006

Regularities in data from factorial experiments

摘要

AI总结

期刊

机构

引用论文