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Using the Net Benefit Regression Framework to Teach Regression

Jeffrey S. Hoch, PhD, Department of Epidemiology and Biostatistics, University of Western Ontario, Schulich School of Medicine, Kresge Building, London, ON N6A 5C1, Canada, (519) 661-2111 x86270, jeffhoch@biostats.uwo.ca

When teaching statistics, examples often speak louder than proofs. However, the challenge facing instructors is to find examples that resonate with students. Examples focusing on health or money may work especially well because generally everyone wants more of both. Examples from the field of economic evaluation offer students an opportunity to study both health and money simultaneously.

The conventional statistic in economic evaluation is the incremental cost-effectiveness ratio (ICER). As a ratio, the estimator’s statistical properties do not make for easy material suitable for an introductory statistics class. However, the net benefit, a recently proposed alternative to the ICER is a linear combination of the parts of the ICER. As a result, it can be used in the net benefit regression framework (NBRF) to illustrate simple, fundamental statistical themes in regression.

This poster briefly reviews economic evaluation and introduces the net benefit statistic. Subsequently, we motivate the net benefit regression framework (NBRF) as proposed by Hoch et al. (2002). Our treatment of the subject is designed to facilitate the introduction of regression concepts in an introductory statistics course.

Learning Objectives: The poster is designed to assist viewers in being able to

Keywords: Economic Analysis, Statistics

Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.

Statistical Software, Estimation and Data Resources -- Posters I

The 132nd Annual Meeting (November 6-10, 2004) of APHA