Calibrated Peer Review for Interpreting Linear Regression Parameters: Results from a Graduate Course


Authors: 
Felicity B. Enders, Sarah Jenkins, and Verna Hoverman
Volume: 
18(2)
Pages: 
online
Year: 
2010
Publisher: 
Journal of Statistics education
URL: 
http://www.amstat.org/publications/jse/v18n2/enders.pdf
Abstract: 

Biostatistics is traditionally a difficult subject for students to learn. While the mathematical aspects are challenging, it can also be demanding for students to learn the exact language to use to correctly interpret statistical results. In particular, correctly interpreting the parameters from linear regression is both a vital tool and a potentially taxing topic. We have developed a Calibrated Peer Review (CPR) module to aid in learning the intricacies of correct interpretation for continuous, binary, and categorical predictors. Student results in interpreting regression parameters for a continuous predictor on midterm exams were compared between students who had used CPR and historical controls from the prior course offering. The risk of mistakenly interpreting a regression parameter was 6.2 times greater before the introduction of the CPR module (p=0.04). We also assessed when learning took place for a specific item for three students of differing capabilities at the start of the assignment. All three demonstrated achievement of the goal of this assignment; that they learn to correctly evaluate their written work to identify mistakes, though one did so without understanding the concept. For each student, we were able to qualitatively identify a time during their CPR assignment in which they demonstrated this understanding.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education

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