Monthly Archives: December 2017

PMean: Another big data publication

I dislike the term “big data” because it implies a class of problems that are immune from normal statistical considerations. I will admit that certain concepts such as the p-value become meaningless when you have millions of observations. But other concepts, like selection bias become even more important for big data.

Anyway, I now have a second publication that is directly tied to the big data movement. Continue reading

PMean: My research interests in 450 characters or less.

I am currently looking for a full-time position. I have been part-time since 2008, because of child care issues. That will change in July 2018 when my wife retires. She’s looking forward to retirement, but I’m the sort of person who will leave my office only in a coffin. Anyway, I’ve updated my resume and written statements on teaching philosophy and on research interests. Those are up in a special spot on my blog, but I also wanted to add a blog entry with a recent request to summarize my research interests in 450 characters or less. Good grief! Any worse, and I could post it on Twitter. Anyway here it is. Continue reading

Recommended: Designing and conducting semi-structured interviews for research

This is a very helpful guide on collecting qualitative data through a semi-structured interview. It emphasizes the need for probe questions and on behaviors that you should adopt to put your subject at ease and get the best information possible. This handout was developed for a college course on Organizational Communication, and the syllabus for this class has other valuable resources. Continue reading

Recommended: No more rainbows

This is a nice article explaining why using a rainbow (red-orange-yellow-green-blue-indigo-violet) is a bad idea. The colors produce an artefactual banding pattern, they do not follow a consistent trend from light to dark, they cause trouble for people with color blindness, and they translate poorly to black-and-white reproductions. The article also shows some nice alternatives. Thanks to @EarlGlynn for sharing this. Continue reading

Recommended: Network analysis in cross-sectional data using R

These are the slides for a very nice webinar presented by Eiko Fried. Dr. Fried provided a wealth of resources during his webinar (some of these are behind pay walls).

He offered examples of network analysis in the study of bereavement and depression and of post-traumatic stress disorder. He also provided tutorial papers on network models with binary data and regularized partial correlation networks., as well as a nice general overview of network models in mental health. He shared a blog posting on the relationship between a latent variable model and a network model and a facebook page on psychological dynamics. He also showed analyses from several R packages, qgraph, IsingFit, and bootnet. I’m putting those links here so I don’t lose track of them when I revisit this stuff six months from now.

Continue reading