We had 36 submissions for the March caption contest that featured a cartoon showing two professionals in front of a giant spinner with various variable names (age; shoe size; tobacco; fever; and vitamin C) - the spinner appears to be landing on "age".
The March caption contest had two co-winners. The first was “Let's see what The Wheel of Non-Causal Relationships comes up with this month for strongest predictor of disease X,” written by Michael Posner from Villanova University and chosen for it’s theme about model building and the inferences that might be drawn in observational studies. The co-winning caption: “I'll go tell the patient it's her age making her sick today. Good thing I don't have to explain that it's her big feet!“ was written by Michele Balik-Meisner, a student at North Carolina State University was selected for its humorous nature and the ability to use the cartoon to discuss how evidence should be examined in light of the associated science (e.g. there might be science behind a causal relationship between some of the variables on the spinner and an illness – but certainly not with shoe size).
Honorable mentions this month go to Mickey Dunlap from University of Georgia for his caption “No no no! You randomize AFTER you select your research topic!”, to Larry Lesser from The University of Texas at El Paso for his caption “This isn't what I meant by 'random variable!” and to Greg Snow from Brigham Young University for his caption “We find this method of finding "significant" predictors to be quicker than using stepwise regression and it is even slightly more reproducible.” (useful in a course for majors that covers the caveats in using a model building procedure like stepwise regression).