This post translates the Stata code to calculate the standard error of the predictions contained in the document, How are average marginal effects and their standard errors computed by margins using the delta method? by Jeff Pitblado of StataCorp, into R code.

Over the weekend, jeremy posted about beckieball, a "new sport sweeping the country." The purpose was to show how selection on characteristics affects the correlation between characteristics upon selection. This, as commenter Stuart Buck pointed out, is an example of Berkson's Paradox, though it relates to jeremy's post about height and nba.

Although he left several other exercises to the reader, I thought I would do a simpler one: recreate the code that he used to make his example. I did this a) because it was a semi-useful way to shake the cobwebs from egg nog and yuletides, and b) because I think that it will come ...

I am currently preparing a proposal for submission and one piece of information that the agency suggests is the power required to distinguish effects. This is obviously a perfectly reasonable piece of information to request; however, power calculations fall into that class of things that I know that I should know but I don't. It is one of those topics that every statistics book will tell you is important, but either a) glosses over the topic, or b) provides such a deep background that it is impossible to follow what the authors are talking about. Additionally, power calculations are complicated enormously by the fact that sample designs can become very ...