Philosophy of Science 71 (5):833-845 (2004)
|Abstract||Over the last two decades, a fundamental outline of a theory of causal inference has emerged. However, this theory does not consider the following problem. Sometimes two or more measured variables are deterministic functions of one another, not deliberately, but because of redundant measurements. In these cases, manipulation of an observed defined variable may actually be an ambiguous description of a manipulation of some underlying variables, although the manipulator does not know that this is the case. In this article we revisit the question of precisely characterizing conditions and assumptions under which reliable inference about the effects of manipulations is possible, even when the possibility of “ambiguous manipulations” is allowed.|
|Keywords||No keywords specified (fix it)|
|Through your library||Configure|
Similar books and articles
Jiji Zhang & Peter Spirtes (2008). Detection of Unfaithfulness and Robust Causal Inference. Minds and Machines 18 (2).
Debra Parrish & Bridget Noonan (2009). Image Manipulation as Research Misconduct. Science and Engineering Ethics 15 (2).
Peter Spirtes, Christopher Meek & Thomas Richardson, Causal Inference in the Presence of Latent Variables and Selection Bias.
Peter Spirtes (2005). Graphical Models, Causal Inference, and Econometric Models. Journal of Economic Methodology 12 (1):3-34.
Added to index2009-01-28
Total downloads5 ( #160,204 of 549,005 )
Recent downloads (6 months)1 ( #63,327 of 549,005 )
How can I increase my downloads?