Author

Jian Cao
3
Gap analysis of JMP for marketing and consumer research

One of the key application areas for JMP is consumer and market research. As I was invited to give a presentation on JMP for marketing analytics, I was curious about how complete the capabilities of JMP are. I wondered whether there are any significant gaps. At a recent American Marketing Association conference

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How late is this year's Chinese New Year?

This year, Chinese New Year arrives on Feb. 19. From what I can remember, this is quite late. But how late is it exactly? I was curious to find out, so I turned to the Internet and found a website that has collected Chinese New Year information since 1900. I

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JMP Pro for linear mixed models — Part 3

This is the final post in my JMP for Linear Mixed Models series (see my earlier posts: Part 1 and Part 2). Here, I will show an example of spatial regression, followed by some tips for fitting mixed models in JMP Pro.  Example 4: Modeling geospatial data — taking spatial

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JMP Pro for linear mixed models — Part 2

In an earlier blog post, I introduced the new Mixed Model capability in JMP Pro 11 and showed an example of random coefficient models. In this post, I continue my discussion of using mixed models for repeated measures and panel data. I’ll leave modeling geospatial data as well as tips

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JMP Pro for linear mixed models — Part 1

JMP Pro 11 has added a new modeling personality, Mixed Model, to its Fit Model platform. What’s a mixed model? How does JMP Pro fit such a model? What are the key applications where mixed models can be applied? In this and future blog posts, I will try to dispel