Quality Progress - March 2018 - 53

still being able to get preliminary
answers to fundamental questions
early in the experiment.
A note on choosing which blocks
to run first: In the DSD case, only
block one has all of the factors at
all of their levels. So if this is one
of the objectives to assess early
in the experiment, choosing block
one to implement first is important. If several blocks satisfy this
objective, their relative D-efficiency
for the main effects model can
be considered when choosing
between alternatives. Sequential
experimentation is an important
aspect to consider when designing
an experiment: If we are able to
learn how the experiment is going
early on, we can adapt if needed to
maximize the information that we
are able to gain.
While randomization may seem
like a small part of the overall
plan for implementing a designed
experiment, it is important to
protect against systematic bias and
to justify the interpretation of the
analysis results.
A completely randomized experiment is the simplest way to include
this in your experiment plan, but
blocking or split-plot designs
provide alternatives to match the
needs of the study.
REFERENCES
1. Klaus Hinkelmann and Oscar
Kempthorne, Design and Analysis
of Experiments, Vol. 1: Introduction
to Experimental Design, WileyInterscience, 1994, pp. 162-168.
2. Christine M. Anderson-Cook, "What
and When to Randomize," Quality
Progress, March 2006, pp. 59-62.
3. Douglas C. Montgomery, Design and
Analysis of Experiments, eighth edition,
Wiley, 2012, pp.139-157.
4. Raymond H. Myers, Douglas C.
Montgomery and Christine M.
Anderson-Cook, Response Surface
Methodology: Process and Product
Optimization Using Designed
Experiments, Wiley-Interscience, 2016,
p. 139 and p. 142.

5. Bradley Jones and Christopher J.
Nachtsheim, "Split-Plot Designs: What,
Why and How," Journal of Quality
Technology, Vol. 41, No. 4, 2009, pp.
340-361.
6. Peter Goos, The Optimal Design of Blocked
and Split-Plot Experiments, Springer, 2012.
7. Myers, Response Surface Methodology:
Process and Product Optimization Using
Designed Experiments, see reference 4, pp.
141-145.
8. Christine M. Anderson-Cook, "When
Should You Consider a Split-Plot Design?"
Quality Progress, October 2007, pp. 57-59.
9. Bradley Jones and Christopher J.
Nachtsheim, "A Class of Three-Level
Designs for Definitive Screening in the
Presence of Second-Order Effects,"
Journal of Quality Technology, Vol. 43, No.
1, 2011, pp. 1-15.
10. Bradley Jones and Christopher J.
Nachtsheim, "Definitive Screening Designs
With Added Two-Level Categorical
Factors," Journal of Quality Technology,
Vol. 45, No. 2, 2013, pp. 121-129.

Christine M. Anderson-Cook
is a research scientist in the
Statistical Sciences Group at Los
Alamos National Laboratory in
Los Alamos, NM. She earned a
doctorate in statistics from the
University of Waterloo in Ontario,
Canada. Anderson-Cook is a
fellow of ASQ and the American
Statistical Association. She is
the 2018 recipient of the ASQ
Shewhart Medal.

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Table of Contents for the Digital Edition of Quality Progress - March 2018

Seen and Heard
Expert Answers
Progress Report
Mr. Pareto Head
Career Coach
My Quality Story
In the Right Direction
A Different Kind of BBQ
Gaining Ground
Impeding Progress
Innovation Imperative
Statistics Spotlight
Standard Issues
Marketplace
Footnotes
Back to Basics
Quality Progress - March 2018 - INTRO
Quality Progress - March 2018 - cover1
Quality Progress - March 2018 - cover2
Quality Progress - March 2018 - 1
Quality Progress - March 2018 - 2
Quality Progress - March 2018 - 3
Quality Progress - March 2018 - 4
Quality Progress - March 2018 - 5
Quality Progress - March 2018 - Seen and Heard
Quality Progress - March 2018 - 7
Quality Progress - March 2018 - Expert Answers
Quality Progress - March 2018 - 9
Quality Progress - March 2018 - Progress Report
Quality Progress - March 2018 - 11
Quality Progress - March 2018 - 12
Quality Progress - March 2018 - Mr. Pareto Head
Quality Progress - March 2018 - Career Coach
Quality Progress - March 2018 - 15
Quality Progress - March 2018 - My Quality Story
Quality Progress - March 2018 - 17
Quality Progress - March 2018 - In the Right Direction
Quality Progress - March 2018 - 19
Quality Progress - March 2018 - 20
Quality Progress - March 2018 - 21
Quality Progress - March 2018 - 22
Quality Progress - March 2018 - 23
Quality Progress - March 2018 - A Different Kind of BBQ
Quality Progress - March 2018 - 25
Quality Progress - March 2018 - 26
Quality Progress - March 2018 - 27
Quality Progress - March 2018 - 28
Quality Progress - March 2018 - 29
Quality Progress - March 2018 - 30
Quality Progress - March 2018 - 31
Quality Progress - March 2018 - Gaining Ground
Quality Progress - March 2018 - 33
Quality Progress - March 2018 - 34
Quality Progress - March 2018 - 35
Quality Progress - March 2018 - 36
Quality Progress - March 2018 - Impeding Progress
Quality Progress - March 2018 - 38
Quality Progress - March 2018 - 39
Quality Progress - March 2018 - 40
Quality Progress - March 2018 - 41
Quality Progress - March 2018 - 42
Quality Progress - March 2018 - 43
Quality Progress - March 2018 - Innovation Imperative
Quality Progress - March 2018 - 45
Quality Progress - March 2018 - 46
Quality Progress - March 2018 - 47
Quality Progress - March 2018 - Statistics Spotlight
Quality Progress - March 2018 - 49
Quality Progress - March 2018 - 50
Quality Progress - March 2018 - 51
Quality Progress - March 2018 - 52
Quality Progress - March 2018 - 53
Quality Progress - March 2018 - Standard Issues
Quality Progress - March 2018 - 55
Quality Progress - March 2018 - 56
Quality Progress - March 2018 - 57
Quality Progress - March 2018 - Marketplace
Quality Progress - March 2018 - 59
Quality Progress - March 2018 - Footnotes
Quality Progress - March 2018 - 61
Quality Progress - March 2018 - 62
Quality Progress - March 2018 - 63
Quality Progress - March 2018 - Back to Basics
Quality Progress - March 2018 - cover3
Quality Progress - March 2018 - cover4
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