Skip to main content

Reproducibility in Research

This post by Mario Pineda-Krch complains about the woeful lack of reproducibility in computational sciences.

This reminded me of Jake Bowers's good piece in the Political Methodologist from earlier this year about how to do reproducible computational political science. The article actually inspired me to completely switch over all of my new writing to Sweave. Sweave allows you to combine your R code and LaTeX documents. If you make your Sweave document and data available to readers they can completely reproduce everything in your article: the models, the table, the graphs, everything. 

RStudio makes using Sweave really easy (though I still use a text editor for writing much of the code since RStudio doesn't do spellcheck). 

Political economy and political science journals don't seem to have been keeping up with these developments. In fact, poli sci journals often require MS Word documents and don't allow you to submit Sweave documents. Few journal submission systems even allow authors to submit data and code appendixes before the paper has been accepted or R&R-ed.

Comments

Popular posts from this blog

Showing results from Cox Proportional Hazard Models in R with simPH

Update 2 February 2014: A new version of simPH (Version 1.0) will soon be available for download from CRAN. It allows you to plot using points, ribbons, and (new) lines. See the updated package description paper for examples. Note that the ribbons argument will no longer work as in the examples below. Please use type = 'ribbons' (or 'points' or 'lines'). Effectively showing estimates and uncertainty from Cox Proportional Hazard (PH) models, especially for interactive and non-linear effects, can be challenging with currently available software. So, researchers often just simply display a results table. These are pretty useless for Cox PH models. It is difficult to decipher a simple linear variable’s estimated effect and basically impossible to understand time interactions, interactions between variables, and nonlinear effects without the reader further calculating quantities of interest for a variety of fitted values.So, I’ve been putting together the simPH R p…

Slide: one function for lag/lead variables in data frames, including time-series cross-sectional data

I often want to quickly create a lag or lead variable in an R data frame. Sometimes I also want to create the lag or lead variable for different groups in a data frame, for example, if I want to lag GDP for each country in a data frame.I've found the various R methods for doing this hard to remember and usually need to look at old blogposts. Any time we find ourselves using the same series of codes over and over, it's probably time to put them into a function. So, I added a new command–slide–to the DataCombine R package (v0.1.5).Building on the shift function TszKin Julian posted on his blog, slide allows you to slide a variable up by any time unit to create a lead or down to create a lag. It returns the lag/lead variable to a new column in your data frame. It works with both data that has one observed unit and with time-series cross-sectional data.Note: your data needs to be in ascending time order with equally spaced time increments. For example 1995, 1996, 1997. ExamplesNot…

Do Political Scientists Care About Effect Sizes: Replication and Type M Errors

Reproducibility has come a long way in political science. Many major journals now require replication materials be made available either on their websites or some service such as the Dataverse Network. Most of the top journals in political science have formally committed to reproducible research best practices by signing up to the The (DA-RT) Data Access and Research Transparency Joint Statement.This is certainly progress. But what are political scientists actually supposed to do with this new information? Data and code availability does help avoid effort duplication--researchers don't need to gather data or program statistical procedures that have already been gathered or programmed. It promotes better research habits. It definitely provides ''procedural oversight''. We would be highly suspect of results from authors that were unable or unwilling to produce their code/data.However, there are lots of problems that data/code availability requirements do not address.…