Title:      Regression Adjustments to Experimental Data: Do David
Freedman�s Concerns Apply to Political Science?

Authors:    Donald Green

Entrydate:  2009-07-15 05:46:17

Keywords:   Experiments, Regression, Covariates, Analysis of
Covariance

Abstract:   Abstract: One of David Freedman�s important
legacies was to raise awareness of the assumptions that underlie
everyday statistical practice, such as regression analysis. His
recent papers (Freedman 2008a, 2008b) offer stern warnings to
those who offer regression analysis as an appropriate way to
analyze experimental results. In particular, Freedman
demonstrates that including pre-treatment covariates as controls
leads to bias in finite samples and inaccurate standard errors.
Freedman advises researchers against using regression
adjustments for experiments involving fewer than 500
observations (2008a, p.191), a recommendation that has gained
increasing attention and acceptance among social scientists.
This paper argues that the ever-cautious Freedman was probably
too cautious in his recommendations. After explicating the
special features of Freedman�s model, I use a combination
of simulated and actual examples to show that as a practical
matter the biases that Freedman pointed out tend to be
negligible for N > 20. Pathological cases that could generate
biases for larger experiments involve extreme outliers that
would be readily detected through visual inspection.

http://polmeth.wustl.edu/retrieve.php?id=917

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