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Using spatial considerations in the analysis of experiments

Journal Article


Abstract


  • Classical experimental design is based on the three concepts of randomization, blocking, and replication. Randomization endeavors to neutralize the effects of (spatial) correlation and yields valid tests for the hypothesis of equal treatment effects. More recently, attempts have been made to use the spatial location of treatments to improve the efficiencies of estimators of treatment contrasts. In this article, we show that a simple, flexible spatial-modeling approach to the analysis of industrial experiments (e.g., wafer fabrication) can yield more efficient estimators of the treatment contrasts than the classical approach. We base the analysis on empirical generalized least squares estimation, in which the spatial-dependence parameters are estimated from resistantly detrended response data. © 1991 American statistical association and the American society for quality control.

Publication Date


  • 1991

Citation


  • Grondona, M. O., & Cressie, N. (1991). Using spatial considerations in the analysis of experiments. Technometrics, 33(4), 381-392. doi:10.1080/00401706.1991.10484867

Scopus Eid


  • 2-s2.0-0003304156

Web Of Science Accession Number


Start Page


  • 381

End Page


  • 392

Volume


  • 33

Issue


  • 4

Abstract


  • Classical experimental design is based on the three concepts of randomization, blocking, and replication. Randomization endeavors to neutralize the effects of (spatial) correlation and yields valid tests for the hypothesis of equal treatment effects. More recently, attempts have been made to use the spatial location of treatments to improve the efficiencies of estimators of treatment contrasts. In this article, we show that a simple, flexible spatial-modeling approach to the analysis of industrial experiments (e.g., wafer fabrication) can yield more efficient estimators of the treatment contrasts than the classical approach. We base the analysis on empirical generalized least squares estimation, in which the spatial-dependence parameters are estimated from resistantly detrended response data. © 1991 American statistical association and the American society for quality control.

Publication Date


  • 1991

Citation


  • Grondona, M. O., & Cressie, N. (1991). Using spatial considerations in the analysis of experiments. Technometrics, 33(4), 381-392. doi:10.1080/00401706.1991.10484867

Scopus Eid


  • 2-s2.0-0003304156

Web Of Science Accession Number


Start Page


  • 381

End Page


  • 392

Volume


  • 33

Issue


  • 4