Monthly Archives: February 2015

Recommended: Editorial (Basic and Applied Social Psychology)

Recommended does not always mean that I agree with what’s written. In this case, it means that this is something that is important to read because it offers an important perspective. And this editorial offers the perspective that all p-values and all confidence intervals are so fatally flawed that they are banned from all future publications in this journal. The editorial goes further to criticize most Bayesian methods because of the problems with the “Laplacian assumption.” The editorial authors have trouble with some of the ambiguities associated with creating a non-informative prior distribution that is, a prior distribution that represents a “state of ignorance.” They will accept Bayesian analyses on a case by case basis. Throwing out most Bayesian analyses, all p-values, and all confidence intervals makes you wonder what they will accept. They suggest larger than typical sample sizes, strong descriptive statistics (which they fail to define), and effect sizes. They believe that by “banning the NHSTP will have the effect of increasing the quality of submitted manuscripts by liberating authors from the stultified structure of NHSTP thinking thereby eliminating an important obstacle to creative thinking.” It’s worth debating this issue, though I think that these recommendations are far too extreme. Continue reading

Recommended: New R Package: cdcfluview

I work a lot with secondary datasets and I’m always looking for new and interesting resources. There is a CDC site that tracks flu reports and with a bit of effort, you can get the raw data behind these reports. A blogger, hrbrmstr (Bob Rudis, if you dig long enough to find his real name), developed an R package that makes it easy to import this data into R. He illustrates the use of this package with a graph that shows some interesting trend lines across several major cities. Continue reading