Author Archives: Jason

Pearson’s r: Not a good measure of electoral persistence

Posted on December 30, 2012 by Jason

Pearson’s product-moment correlation, \(r\), is an incredibly useful tool for getting some idea about how two variables are (linearly) related. But there are times when using Pearson’s \(r\) is not appropriate and, even if linearity and all other assumptions hold, … Continue reading →

Posted in Data analysis, Graphics, Poland, Political parties, R | 1 Comment

R Tip: Avoid using T and F as synonyms for TRUE and FALSE

Posted on December 11, 2012 by Jason

By default when you start R, T and F are defined as TRUE and FALSE. When I review other people’s code, I often see functions defined with arguments set to these values by default. This is a very bad idea. … Continue reading →

Posted in Hacking, R, Tip | 1 Comment

Closures in R: A useful abstraction

Posted on December 2, 2012 by Jason

People who have been using R for any length of time have probably become accustomed to passing functions as arguments to other functions. From my experience, however, people are much less likely to return functions from their own custom code. … Continue reading →

Posted in R | 1 Comment

Filtering a list with the Filter higher-order function

Posted on January 26, 2012 by Jason

Last week markbulling over at Drunks & Lampposts posted a method of using sapply to filter a list by a predicate. Today the @RLangTip tip of the day was to use sapply similarly. This made makes me wonder if R‘s … Continue reading →

Posted in R | Leave a comment

Announcing boolean3 (beta)

Posted on January 24, 2012 by Jason

After entirely too long, I am happy to announce the beta release of boolean3, an R package for modeling causal complexity. The package can be downloaded at the following links: Unix/Linux: boolean3_3.0.20.tar.gz Windows: boolean3_3.0.20.zip (Please let me know if you have any … Continue reading →

Posted in Code, R | 1 Comment

Welford’s method for calculating the sample variance: An implementation in Scheme

Posted on December 17, 2011 by Jason

John Cook has three entries up on his blog discussing the pitfalls of calculating the sample variance using the mathematical textbook definitions. He provides a Monte Carlo comparison of methods here, and a theoretical discussion here. He also provides a … Continue reading →

Posted in Code, Data analysis, Scheme | Leave a comment

Three free books for better programming in R (and any other language)

Posted on September 19, 2011 by Jason

Like many users and producers of R packages, I have never had any formal training in computer science. I’ve come to to the conclusion that this is a serious omission in a professional researcher’s training. Computer scientists and professional hackers … Continue reading →

Posted in Hacking, R | 4 Comments

The performance cost of a for-loop, and some alternatives

Posted on August 21, 2011 by Jason

I’ve recently been spending a lot of time running various simulations in R. Because I often use snow to perform simulations across several computers/cores, results typically come back in the form of a list object. Summarizing the results from a list … Continue reading →

Posted in R | 10 Comments

Emacs-fu: The place to go for useful Emacs tips

Posted on August 19, 2011 by Jason

After 5 years or so of using Emacs almost exclusively as my “text editor”, somehow I just ran across Emacs-fu for the first time today. It’s an incredibly useful site with numerous Emacs tips and tricks. If you are an Emacs user, you should check the … Continue reading →

Posted in Emacs, Hacking | Leave a comment

Stronger instruments by design: Polmeth 2011 poster

Posted on July 31, 2011 by Jason

I just got back from Polmeth 2011 at Princeton, where I presented a poster for a project Luke Keele and I are working on. It deals with the problem of statistical inference in the presence of a weak instrument and the … Continue reading →

Posted in Causal inference, Instrumental variables, Matching | Leave a comment