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Showing posts from April, 2013

Reinhart & Rogoff: Everyone makes coding mistakes, we need to make it easy to find them + Graphing uncertainty

You may have already seen a lot written on the replication of Reinhart & Rogoff’s (R &amp R) much cited 2010 paper done by Herndon, Ash, and Pollin . If you haven’t, here is a round up of some of some of what has been written: Konczal , Yglesias , Krugman , Cowen , Peng , FT Alphaville . This is an interesting issue for me because it involves three topics I really like: political economy, reproducibility, and communicating uncertainty. Others have already commented on these topics in detail. I just wanted to add to this discussion by (a) talking about how this event highlights a real need for researchers to use systems that make finding and correcting mistakes easy, (b) incentivising mistake finding/correction rather than penalising it, and (c) showing uncertainty . Systems for Finding and Correcting Mistakes One of the problems Herndon, Ash, and Pollin found in R&R’s analysis was and Excel coding error . I love to hate on Excel as much as the next R devotee, but

Dropbox & R Data

I'm always looking for ways to download data from the internet into R. Though I prefer to host and access plain-text data sets (CSV is my personal favourite) from GitHub (see my short paper on the topic) sometimes it's convenient to get data stored on Dropbox . There has been a change in the way Dropbox URLs work and I just added some functionality to the repmis R package. So I though that I'ld write a quick post on how to directly download data from Dropbox into R. The download method is different depending on whether or not your plain-text data is in a Dropbox Public folder or not. Dropbox Public Folder Dropbox is trying to do away with its public folders. New users need to actively create a Public folder. Regardless, sometimes you may want to download data from one. It used to be that files in Public folders were accessible through non-secure (http) URLs. It's easy to download these into R, just use the read.table command, where the URL is the file name