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The Limits of Causal Inference from Observational Peter Spirtes
 

Summary: The Limits of Causal Inference from Observational
Data
Peter Spirtes
Carnegie Mellon University
ps7z@andrew.cmu.edu

2
1. Introduction
The following quotation from Rosenbaum (1995) expresses a commonly held view
about the problem of potential confounders, and how they can be dealt with. (We will
take a ``confounder'' of treatment and response to be a variable that is a cause of both
treatment and response.)
An observational study is an empirical investigation of treatments, policies, or
exposures and the effect they cause, but it differs from an experiment in that the
investigator cannot control the assignment of treatments to subjects. ... Analytical
adjustments are widely used in observational studies to remove overt biases, that
is, differences between treated and control groups, present before treatment, that
are visible in the data at hand. ... If treated and control groups differed before
treatment in ways not recorded, there would be a hidden bias. ... sensitivity
analyses ... ask how the findings of a study might be altered by hidden biases of

  

Source: Andrews, Peter B. - Department of Mathematical Sciences, Carnegie Mellon University

 

Collections: Mathematics