JMPer Cable Current Issue (Summer 2014)

JMPer Cable is a technical publication for users of JMP software.

Cover Story: Informative Missing Regression Coding in JMP® 11

John Sall, Co-Founder and Executive Vice President, SAS

What if I told you that by adding a very simple feature, you could fit many models more accurately than before? At the same time, I could show you that your previous answers were very biased, but the new ones were much less biased. Furthermore, rather than just fitting the nonmissing data, you could use all of the data, making predictions even when regressors are missing.

Identifying Quality Issues and Misconduct Using Analyses of Digit Preference (pg. 3)

Richard Zink, PhD, Principal Research Statistician Developer, JMP Life Sciences

The new Digit Preference option in JMP Clinical 5.0 enables you to uncover quality issues and misconduct in clinical trials.

Fast Flexible Filling in Space-Filling Designs (pg. 5)

Bradley Jones, PhD, JMP Principal Research Fellow, SAS
Ryan Lekivetz, JMP Research Statistician Developer, SAS

A new tool in the Space-Filling Design platform supports placing design points in non-rectangular regions. Space-filling designs are very popular in experimentation with complex deterministic computer models. Such models give the same answer if you supply the same inputs, so controlling variability is not an issue.

When Responses Are Below the Limit of Detection (pg. 8)

Mark Bailey, Principal Analytical Training Consultant,
Education and Training, SAS

To learn about a system or a process, there must be variation. If the characteristics or outcomes never change, then it is impossible to learn anything. We design experiments to provoke a large change in the response in the hope that the analysis will be more informative, both in kind (factor effects) and degree (precision).

Generalized Regression in JMP® Pro 11 (pg. 12)

Clay Barker, JMP Senior Research Statistician Developer, SAS

The Generalized Regression platform (new in JMP Pro 11) is designed for fitting penalized generalized linear models. That means that we can build models where the response is not normally distributed (for example, in logistic and Poisson regression models).

Join the JMP® User Community (pg. 14)
The JMP User Community is the largest online community of JMP users. It’s the home of the File Exchange, where you can share and download JMP add-ins, scripts and sample data files.

Designing Insightful Process Behavior Charts (pg. 15)

José G. Ramírez, PhD
Annie D. Zangi, JMP Research Statistician Developer, SAS

In this article, we show how Control Chart Builder can be used to investigate different chart designs, helping select the one that reveals hidden differences in the data.

JMP Books From SAS Press (pg. 19)

Learn about a few of the upcoming JMP titles from SAS Press.

What’s New in JMP® Training (pg. 20)

New courses debut at JMP Discovery Summit 2014. Don’t miss the JMP Discovery Summit, Sept. 15 -18, in Cary, North Carolina, USA. SAS Education offers discounted JMP training to Discovery Summit attendees before and after the conference.

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