Embarrassing Parallelism: I Got 99 Problems, but a Core ain’t One

Somewhat foolishly, my university has granted me access to Mogon: not the god, not the death metal band but rather their supercomputer, which currently holds the 182th spot in the top 500 list of the fastest computers on the planet. It has some 34,000+ cores and more than 80 TB of RAM, but basically it’s just a very large bunch of Linux boxes. That means that I have a rough idea how to handle it, and that it happily runs my native Linux Stata and MPlus (and hopefully Jags) binaries for me. It also has R installed, and this is where my misery began.

Just How Biased is Your Survey? Ask our Stata Add-On (Update)

We have updated our Stata package surveybias, which estimates bias in pre-election polls and other surveys where the true distribution is known. A new feature facilitates the en masse comparison of surveys collected before an election. Also in this release: somewhat better documentation and toy data to get you started.

Stata Software for Assessing Survey Bias

BinaryApe / Foter / CC BYIn a recent paper, we derive various multinomial measures of bias in public opinion surveys (e.g. pre-election polls). Put differently, with our methodology, you may calculate a scalar measure of survey bias in multi-party elections. Thanks to Kit Baum over at Boston College, our Stata add-on surveybias.ado is now available…

A Scalar Measure for Bias in (Multi-Party Pre-Election) Surveys

All surveys deviate from the true distributions of the variables, but some more so than others. This is particularly relevant in the context of election studies, where the true distribution of the vote is revealed on election night. Jocelyn Evans and I present a method for calculating a scalar measure that neatly summarises such bias for multi-party elections. We also present a Stata module that implements our new method.

nlcom and the Delta Method

The delta method approximates the expectation of some function of a random variable by relying on a (truncated) Taylor series expansion. In plain words, that means that one can use the delta method to calculate confidence intervals and perform hypothesis tests on just about every linear or nonlinear transformation of a vector of parameter estimates. Stata’s procedure nlcom is a particularly versatile and powerful implementation of the delta method. If you can write down the formula of the transformation, nlcom will spit out the result. And that means that you can abuse Stata’s built in procedures to implement your own estimators.