Monthly Archives: December 2013

Recommended: Comparison of Logistic Regression versus Propensity Score When the Number of Events Is Low and There Are Multiple Confounders

Propensity scores represent an intriguing alternative method to reduce the impact of confounding variables, especially when there are multiple potential confounding variables. This paper considers a range of models comparing the propensity score approach to the more traditional approaches of adjusting for confounders. I think the conclusions are overly simplistic, but the paper is still worth reading. Continue reading

Recommended: Study Development (Kansas City area resource)

This is an excellent local resource for those of you in the Kansas City area. They have guidance on coming up with a study idea, finding funding,  and identifying study participants. This site offers general information and links to resources with Frontiers (aka the Heartland Institute for Clinical and Translational Research). Continue reading

Recommended: Use = or <- for assignment?

I learned R back when the only way to assign a value was with the <- operator. For example, if you were computing the hypotenuse of a triangle, you’d use c <- sqrt(a^2+b^2). But the language now allows you to use an equals sign instead, which is the choice in many other programming languages. Should you do this? I say “no” emphatically, but this website makes an interesting counter-argument. Continue reading