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Kaufman, Jay S. (2008). Commentary: Why Are We Biased against Bias?. International Journal of Epidemiology, 37(3), 624-626.


Greater attention to causal inference has been one of the most important trends in social epidemiology over the last decade. The groundwork was laid 35 years ago by Mervyn Susser's book ‘Causal Thinking in the Health Sciences’, but growing interest more recently in causal techniques such as potential outcomes models and directed graphs has given the field new capacities for strengthening inference and honing arguments. Many techniques that have been standard in econometrics and the social sciences for years have made their way into social epidemiology in the last decade, including multilevel modeling, propensity score matching and instrumental variables. One such technique, exploited cleverly in the article by Gilman and colleagues, is the fixed effects regression model.


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Journal Article

Year Published


Journal Title

International Journal of Epidemiology


Kaufman, Jay S.