Factorial Experiments With Time Trends


Steinberg, David M.   (1988, ASQC and the American Statistical Association)   Tel-Aviv University, Israel

Technometrics    Vol. 30    No. 3
QICID: 9355    August 1988    pp. 259-269
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Article Abstract

Time trends may affect the results of experiments that are conducted sequentially. A simple, yet powerful, way to model such an experiment is to represent the trend by an autoregressive integrated moving average time series model. I show how such models can be used to jointly estimate factorial and time-order effects and how they can be used as a diagnostic device to detect time trends in complex experiments.


Factorial designs,Statistics,Time series,Spline functions,Polynomial model

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