Article

Challenges for Causal Inference in Obesity Research

M. Christopher Auld and Paul Grootendorst

in The Oxford Handbook of the Social Science of Obesity

Published in print October 2011 | ISBN: 9780199736362
Published online September 2012 | | DOI: http://dx.doi.org/10.1093/oxfordhb/9780199736362.013.0014

Series: Oxford Handbooks

 Challenges for Causal Inference in Obesity Research

More Like This

Show all results sharing these subjects:

  • Economics
  • Health, Education, and Welfare

GO

Show Summary Details

Preview

This chapter reviews the empirical strategies that social scientists commonly use to make causal inferences in the absence of randomized experiments and then highlights particularly challenging issues in obesity research. It provides a non-technical summary of several approaches to making causal inferences when the researcher only has observational data available, that is, data in which the researcher cannot control the values of the treatment of interest. The instrumental variable methods in obesity research are described. Body weight is difficult to measure, in both conceptual and practical senses. It is difficult to explain, making the search for identification through instrumental variables even more difficult than usual and undermining efforts to characterize the causes of body weight itself. Body weight is a stock which changes slowly over time, such that small influences on body weight over time may eventually cause large changes in weight but will be very difficult to detect statistically.

Keywords: obesity; causal inferences; instrumental variable methods; body weight

Article.  7460 words. 

Subjects: Economics ; Health, Education, and Welfare

Full text: subscription required

How to subscribe Recommend to my Librarian

Buy this work at Oxford University Press »

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.