“You should be writing” is the mantra for academics everywhere. But what to do when you committed to writing over the weekend and your reference manager crashes? Freak out, of course! As of 2017-01-28 06:37 GMT, the Mendeley server that syncs references has been returning errors. Here’s what we know about it: Continue reading
Erowid.org is described as “a member-supported organization providing access to reliable, non-judgmental information about psychoactive plants, chemicals, and related issues.” The site was launched in 1995 and by 2005 had 450,000 page hits and 45,000 visitors per day. Website use statistics haven’t been reported since then, though its likely that there has been some attrition due to the growing diversity of online resources for drug information. Out of curiosity, I ran a quick Google Trends search to compare where Internet users are searching for information about two well-known synthetic drugs, LSD (acid) and MDMA (ecstasy). The following chart depicts searches for these two keywords that were accompanied by either “erowid” or “reddit”, as well as a search for “erowid reddit”.
Monthly search data were obtained from January 2004 through the present day and trendlines were smoothed using a logarithmic ^4 transformation. What we see is that sometime in 2015, searches for information about these drugs related to Reddit appeared to overtake searches related to Erowid. Implications of this trend go beyond simple navel-gazing about Internet search preferences. For example, if individuals are now more likely to get information about psychoactive drugs from Reddit, it begs questions about the quality of information that they are getting (particularly information about risks and interactions which is prominent and well-curated on the Erowid site).
I used a D3.js zoomable treemap template to create an interactive visualization of university courses that I’ve taken. The courses are loosely grouped by subject area and subdivided by level (undergraduate vs. graduate). The data are stored in JSON format.
Sometimes it is useful to group similar dichotomous variables together into a single variable. One example is when asking survey respondents to identify race/ethnicity. Given a large, heterogeneous sample, there will undoubtedly be respondents who select two, three, or more racial/ethnic categories. When using checkbox input fields, most survey data collection platforms will store each checkbox value as a distinct variable (False=0, True=1) and provide a data column for each. This can become problematic when you want to report the summary output as mutually-exclusive data (each respondent counted only once).
For the race/ethnicity example, a respondent might click checkboxes for both ‘Black’ and ‘White’ if they identify as biracial. If you tabulate these two variables separately, this person will be counted twice. If you want mutually-exclusive respondent counts, you may want to combine all of the dichotomous variables into a single composite variable that you can then summarize. What follows is a fairly easy way to do that without losing your mind or the nuance of the original variables.
I’ve been on the fence about replacing my broken FitBit for a couple years. What finally pushed me off that fence was the recent unlocking of intraday data for developers’ personal projects. This makes it possible for me to access my minute-by-minute activity and sleep data. What follows is a quick rundown of my initial foray into FitBit sleep tracking. Continue reading