My co-author Robin Lovelace has recently made available a new version of his R package stplanr, which helps processing and visualizing Origin-Destination transport data in R. It integrates the useful dist_google function to get network distances and time using the Google Maps API, which we used in our accessibility to schools in São Paulo paper. Highly recommended!
Great post about introducing students to the fundamental concept of reproducibility in science while teaching them R
A recently published paper by Baumer et al (2014) caught my eye today (HT to Bruce Caron). I wanted to share it here because I thought it was cool and also had a few comments to make about some of the issues the authors raised.
First, a bit about the paper. Partly in response to all the media attention to the crisis in reproducibility in science (e.g. Nature) Baumer and colleagues made some changes to introductory statistics classes at Duke, Smith, and Amherst. The primary change was to require the use of R Markdown for all homework. RStudio was the editor they used and it appears any cutting and pasting of code, figures, etc. was not allowed. They conducted a survey of the students early in the class and after the class. The end result was that students preferred using R Markdown over the typical mode of cut and…
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During the last decade, an increasing number of political scientists have turned to regression-discontinuity (RD) designs to estimate causal effects. Although the growth of RD designs has stimulated a wide discussion about RD assumptions and estimation strategies, there is no single shared approach to guide empirical applications. One of the major issues in RD designs involves selection of the “window” or “bandwidth” — the values of the running variable that define the set of units included in the RD study group. [i]
This choice is key for RD designs, as results are often sensitive to bandwidth size. Indeed, even those who propose particular methods to choose a given window agree that “irrespective of the manner in which the bandwidth is chosen, one should always investigate the sensitivity of the inferences to this choice. […] [I]f the results…
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Erik Marcon, Stephane Traissac, Florence Puech and Gabriel Lang have developed the R package dbmss that provides a toolbox to characterize point patterns. The package greatly simplifies the task of obtaining distance-based agglomeration and coagglomeration indexes, such as the Duranton and Overman’s Kd function and the Marcon and Puech’s M functions.