I don’t have time to provide extensive citations for this post, so some things are cited from memory. You should be able to locate the relevant literature, but otherwise just ask. Haier, R. J. (2016). The Neuroscience of Intelligence (1 edition). New York, NY: Cambridge University Press. Because I’m writing a neuroscience-related paper or two, […]

This is commentary on: Ellis, L., Hoskin, A. W., Dutton, E., & Nyborg, H. The Future of Secularism: a Biologically Informed Theory Supplemented with Cross-Cultural Evidence. Evolutionary Psychological Science, 1-19. For over a century, social scientists have predicted declines in religious beliefs and their replacement with more scientific/naturalistic outlooks, a prediction known as the secularization […]

Lots of published psychology studies don’t replicate well, in particular cute things like interactions, counter-intuitive or priming effects. In general, traditional behavioral genetics studies have replicated well. This is not surprising because basically the same method (ACE fitting) has been applied to lots of large datasets, and studies that use consistent methods on large datasets […]

There seem to be ways to post knitr documents to WordPress blogs, but until that’s set up, I will be publishing them over at RPubs and posting a link here. The post begins like this: In a post published on his website, Gwern investigates the efficiency of embryo selection. It’s impressive work. In a later […]

In the spirit of reproducible science, this is a post about an error I fixed in a function that affects all prior analyses with that. When factor analyzing data, the goal is to reveal a latent structure in the dataset. Given various assumptions, factor analysis will find a structure if there is one. It is […]

I’m reading Missing Data: A Gentle Introduction and it mentions various methods to understand how data are missing in a given dataset. The book, however, is light on actual tools. So, since I have already implemented a few functions in my package for handling missing data, I decided to implement a few more. These have […]

Suppose you have some dataset where you know or suspect that the real generating function is actually a piecewise function with k pieces each of which is a standard linear model. How does you find these? This is the problem presented to me from a friend. I came up with this method: Find all the […]

Someone asks on Reddit: Can someone intuitively explain the correlation formula? I know what the Cov(X,Y) means. It tells you if the relationship between the variables X and Y is positive or negative (although I must admit I dont really know what the actual number means, I only look the the sign). I know what […]

When one has a continuous variable and then cuts it into bins (discretization) and correlates it with some other variable, the observed correlation is biased downwards to some extent. The extent depends on the cut-off value(s) used and the number of bins. Normally, one would use polychoric-type methods (better called latent correlation estimation methods) to […]