ENBIS-18 in Nancy

2 – 25 September 2018; Ecoles des Mines, Nancy (France) Abstract submission: 20 December 2017 – 4 June 2018

Using Split-Plot Diagnostics to Reveal Hidden Information

3 September 2018, 11:30 – 12:00

Abstract

Submitted by
Pat Whitcomb
Authors
Pat Whitcomb (Stat-Ease, Inc.)
Abstract
The aim of this talk is to motivate DOE practitioners to use RSM split-plot designs while properly accounting for fixed effects for the model coefficients and random effects for the variance components.

By way of a case study, this talk features innovative diagnostics for split-plot designs that reveal outliers and other abnormalities. These diagnostics are derived from restricted maximum likelihood (REML) tools that estimate fixed factor effects and random variance components. The presentation begins by laying out the benefits of split-plot designs versus traditional response surface method (RSM). It then demonstrates how diagnostic plots tailored for split-plot designs can reveal surprising wrinkles in experimental data.
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