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Issue:
Volume 9, Number 11
Date:
November 2009
From:
Mark J. Anderson, Stat-Ease, Inc., Statistics Made Easy® Blog
Dear Experimenter,
Here's another set of frequently asked questions (FAQs) about doing design of experiments (DOE), plus alerts to timely information and free software updates. If you missed the previous DOE FAQ Alert, see below.
==> Tip: Get immediate answers to questions about DOE via the Search feature on the main menu of the Stat-Ease® web site. This not only pores over previous alerts, but also the wealth of technical publications posted throughout the site.
Feel free to forward this newsletter to your colleagues. They can subscribe by going to http://www.statease.com/doealertreg.html. If this newsletter prompts you to ask your own questions about DOE, please address them via mail to: [email protected].
Also, Stat-Ease offers an interactive web site—the Support Forum for Experiment Design at http://forum.statease.com. Anyone (after gaining approval for registration) can post questions and answers to the Forum, which is open for all to see (with moderation). Furthermore, the Forum provides program help for Design-Ease® and Design-Expert® software. Check it out and search for answers. If you come up empty, do not be shy: Ask your question! Also, this being a forum, we encourage you to weigh in!
For an assortment of appetizers to get this Alert off to a good start, follow this link, http://www.StatsMadeEasy.net* (-> new web site!), and see a number of new blogs (listed below, beginning with the most recent one):
—Statisticians do not see global cooling trend
—Experiments for school now safer, but less educational
—NASA shoots the Moon
*Need a feed or e-mail updates from StatsMadeEasy? Go to http://feeds.feedburner.com/StatsMadeEasy. It's easy!
"Your StatsMadeEasy blogs brighten up a dreary workday!"
—Applied Statistician, Florida
Topics in the body text of this DOE FAQ Alert are headlined below (the "Expert" ones, if any, delve into statistical details).
1. FAQ: Middle levels of factor settings not at center point
2. FAQ: Why does recommended transformation by Box-Cox require a value "k" to make the response positive?
3. Expert-FAQ: How do you interpret the full-cubic term in mixture models?
4. Info Alert: DOE optimizes a bioproduction system
5. Events Alert: Life Science Alley Conference & Expo
6. Workshop Alert: Dynamic duo of DOE-RSM workshops in December—save $395 by attending both
P.S. Quote for the month: Sharpen up your statistical tools.
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1. FAQ: Middle levels of factor settings not at center point
-----Original Question-----
From: Industrial automation professional
"I want to design a four-factor half-fraction or full-factorial two-level design with maybe 3-6 center point runs. For some of my factors, although they cover a wide range, the set point (the equipment is nominally run at) is actually not the mathematical center (median) of the range. I wonder, if instead of "center point runs" I input runs at non-center conditions, would the analysis will still be valid. I think the software will still analyze it, I just don't know what exactly the impact will be."
Answer:
I suggest you simply modify the center point levels to match your standard operating conditions (SOC). You will lose the curvature test provided by Stat-Ease software, but still benefit from the estimate of pure error coming via replication of the SOC.
P.S. from Stat-Ease Consultant Shari Kraber:
"View the 3D surface plot to see how closely the points in the center region are fitted by your predictive model."
P.P.S. from Stat-Ease Consultant Pat Whitcomb:
"Here's a work-around for situations like this: Change the response to be analyzed as a polynomial (rather than factorial model). That adds squared terms, which provide an indication of curvature."
(Learn more about center points by attending the computer-intensive workshop "Experiment Design Made Easy." See http://www.statease.com/clas_edme.html for a description of this class and link from this page to the course outline and schedule. Then, if you like, enroll online.)
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2. FAQ: Why does recommended transformation by Box-Cox require a value "k" to make the response positive?
-----Original Question-----
From: Biomedical engineer
"I have a response ranging from minus to positive values. Using the Box-Cox analysis* Design-Expert software recommends a square root transform (lambda = 0.5), with a k equal to a value somewhat larger in absolute value than my most negative response. The software says this should be used to make response values positive. Please explain what this is all about."
Answer (from Stat-Ease Consultant Wayne Adams):
"The constant k added to the response is required to make all observations positive. Zero is not positive, so the constant does need to be a bit larger than the smallest observation. We calculate the Box-Cox with a larger constant than we really need to prevent rounding and math errors that happen to floating point logic near true zeros. We try to keep it reasonably close, though. The actual method that determines the k value we use is scaled relative to the observations."
*The Engineering Statistics Handbook offers details on Box-Cox at: http://www.itl.nist.gov/div898/handbook/eda/section3/boxcoxno.htm
(Learn more about transformations by attending the computer-intensive workshop "Experiment Design Made Easy." See http://www.statease.com/clas_edme.html for a description of this class and link from this page to the course outline and schedule. Then, if you like, enroll online.)
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3. Expert-FAQ: How do you interpret the full-cubic term in mixture models?
-----Original Question-----
From: An entomologist
"How do you interpret the cubic term AB(A-B) when significant? The interaction between A and B is obviously significant but what does (A-B) mean?"
Answer:
You best simply consider this a shaping term that fits asymmetry in the mixture response surface. For details, refer to "Chapter 1 Appendix: Cubic Equations for Mixture Modeling (and Beyond)" in the "A Primer on Mixture Design: What’s In It for Formulators?" posted at http://www.statease.com/pubs/MIXprimer.pdf. For an expert second-opinion on how you modeled your critical response(s), e-mail your Design-Expert data file (*.dx*) to [email protected]: Seeing the actual data helps us better help you.
(Learn more about modeling responses from mixture experiments by attending the computer-intensive workshop "Mixture Design for Optimal Formulations." For a complete description of this class, see http://www.statease.com/clas_mix.html. Link from this page to the course outline and schedule. Then, if you like, enroll online.)
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4. Info Alert: DOE optimizes a bioproduction system
Steve Peppers details how "DoE Helps Optimize a Cell Culture Bioproduction System" in the October issue of BioProcess International (register and sign in for the full article): http://www.bioprocessintl.com/default.asp?page=supparticles. If you are interested in publishing your DOE story, please contact Heidi via [email protected] or call her 612.746.2033. See our current collection of DOE case studies and articles at http://www.statease.com/articles.html. We are especially in need of applications from the life sciences. Factor details can be coded for secrecy sake, so confidentiality need not be compromised.
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5. Events Alert: Life Science Alley Conference & Expo
Stat-Ease will exhibit new software developments and answer questions about experiment design at the Life Science Alley Conference & Expo in Minneapolis on December 9. This event engages the medical device, health care, pharmaceutical, biopharma, biotechnology, and food and nutrition sectors.* See http://www.lifesciencealleyconference.org/ for details. Click http://www.statease.com/events.html for a list of upcoming appearances by Stat-Ease professionals. We hope to see you sometime in the near future!
(Learn more about applying DOE in these vital industries by attending the computer-intensive workshop "Designed Experiments for Life Sciences." See http://www.statease.com/clas_dels.html for a description of this class and link from this page to the course outline and schedule. Then, if you like, enroll online.)
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6. Workshop Alert: Dynamic duo of DOE-RSM workshops in December — save $395 by attending both
Seats are filling fast for the following DOE classes. If possible, enroll at least 4 weeks prior to the date so your place can be assured. However, do not hesitate to ask whether seats remain on classes that are fast approaching!
—> Experiment Design Made Easy (EDME)
(Detailed at http://www.statease.com/clas_edme.html)
> December 8-9 (Minneapolis, MN) ** ADDED BY POPULAR DEMAND**
—> Response Surface Methods for Process Optimization (RSM)
(http://www.statease.com/clas_rsm.html)
> December 10-11 (Minneapolis, MN)
**Save $395 by attending December EDME-RSM back-to-back**
—> Mixture Design for Optimal Formulations (MIX)
(http://www.statease.com/clas_mix.html)
> March 2-3, 2010 (Minneapolis, MN)
—> Designed Experiments for Life Sciences (DELS)
(http://www.statease.com/clas_dels.html)
> November 10-11, 2009(Cambridge, MA)**SOLD OUT**
> February 23-24, 2010 (Minneapolis, MN)
See http://www.statease.com/clas_pub.html for complete schedule and site information on all Stat-Ease workshops open to the public. To enroll, click the "register online" link on our web site or call Elicia at 612.746.2038. If spots remain available, bring along several colleagues and take advantage of quantity discounts in tuition. Or, consider bringing in an expert from Stat-Ease to teach a private class at your site.**
**Once you achieve a critical mass of about 6 students, it becomes very economical to sponsor a private workshop, which is most convenient and effective for your staff. For a quote, e-mail [email protected].
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
I hope you learned something from this
issue. Address your general questions and comments to me at: [email protected].
PLEASE DO NOT SEND ME REQUESTS TO SUBSCRIBE OR UNSUBSCRIBE—FOLLOW THE INSTRUCTIONS AT THE END OF THIS MESSAGE.
Sincerely,
Mark
Mark J. Anderson, PE, CQE
Principal, Stat-Ease, Inc. (http://www.statease.com)
2021 East Hennepin Avenue, Suite 480
Minneapolis, Minnesota 55413 USA
PS. Quote for the month—sharpen up your statistical tools:
"The universe is full of magical things patiently waiting for our wits to grow sharper."
—Eden Phillpotts
Trademarks:
Stat-Ease, Design-Ease, Design-Expert
and
Statistics Made Easy are registered trademarks of Stat-Ease, Inc.
Acknowledgements to contributors:
—Students of Stat-Ease training and users of Stat-Ease software
—Stat-Ease consultants Pat Whitcomb, Shari Kraber and Wayne Adams
(see http://www.statease.com/consult.html
for resumes)
—Statistical advisor to Stat-Ease: Dr. Gary Oehlert (http://www.statease.com/garyoehl.html)
—Stat-Ease programmers, led by Neal Vaughn and Tryg Helseth
(http://www.statease.com/pgmstaff.html)
—Heidi Hansel Wolfe, Stat-Ease sales and marketing director, and all the remaining
staff that provide such supreme support!
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