PMean: Sentiment analysis of A Christmas Carol

I was at an interesting talk about sentiment analysis and decided to try something simple myself. Sentiment analysis is a text analytics method that compares text data with a list of words with positive or negative sentiments. The relative frequency of the positive or negative words is a crude measure of the general sentiment of the text item. I ran a sentiment analysis on the text of the famous Charles Dickens novel, A Christmas Carol. Continue reading

Recommended: An introduction to implementation science for the non-specialist

I’ve done a lot of work with Evidence-Based Health, but one big and largely unsolved problem is how to get health care professionals to change their practices once the evidence for these changes becomes obvious. If no one changes in the face of evidence, then all the effort to produce and critically appraise the evidence becomes worthless. A new field, implementation science, has been developed to get at methods to encourage the adoption of new evidence-based practices. This paper outlines how implementation science is supposed to work and offers two real world examples of implementation science studies. Continue reading

PMean: Do you need to name your function arguments in R?

If you program anything in R, you’ll end up calling a lot of functions. You pass your data or your constants to these functions, and you can do it in one of two ways. You can either pass the data/constants in the order in which the function expects the arguments or you can match each data/constant value with a particular argument name. This came up in the context of a question: do I need to save everything using

save.image(file=”foo.RData”)

or can I save it with

save.image(“foo.RData”)? Continue reading

PMean: My work on a CTSA grant

I’m on a Clincal and Translational Science Award (CTSA) research grant (5UL1TR000001-05, formerly 1U54RR031295-01A1), which is pretty cool. My name is even mentioned a few times in the grant. I thought that as I plan what I would do for this grant, I would see what the grant promised and write down what, exactly, that those promises mean. As I talk with various people (especially Russ Waitman, who is supervising my work on this grant), I will revise and update my plans. Still, I thought it would be valuable to put some thoughts down now, both to help me focus on what I should be doing and to offer an early draft of those ideas to the various people that I will end up interacting with. Continue reading

Recommended: Hi, I’m Mike Bostock.

This is an AMA (Ask Me Anything) session with Mike Bostock, a former graphics editor for the New York Times and creator of the d3.js data visualization package. I’ll be writing a few things about d3.js once I figure things out. Mike is someone worth watching, because he is working on high visibility, high impact stuff. Continue reading

Recommended: How to be more effective in your professional life

Doug Zahn has done a tremendous amount of work on what I like to call the human factors in statistical consulting. He summarizes some key ideas in this article. His humorous anecdote about his prized Mustang car illustrates the tendency of all of us to be poor listeners. Pay special atention to Table 1 where he outlines the five steps you should always follow in any consulting interaction. Continue reading