data METODE teori — Datoen i dag er: 18.2.2018

Info fra Judea Pearl om noen artikler mm på kausalitet

Av Ronny Klæboe Dato: 9.7.2009

1. A new article, authored by Ilya Shpitser and myself. is now posted on the UCLA Causality-Blog / (see also link_pdf)

It offers a solution to the problem of evaluating “Effects of Treatment on the Treated (ETT)”

The problem is of theoretical interest because ETT,  despite its blatant counterfactual character (e.g., “I just took an aspirin, perhaps I shouldn’t
have?”)  can be evaluated from experimental studies in many,  though not all cases.  Characterizing those cases illuminates therefore the empirical content of counterfactuals.

2.  Many of you have commented on my article “Myth, Confusion and Science in Causal Analysis” (Inspired by a Don Rubin), a revised version of which is now posted on our website.
I would like to encourage a blog-discussion on the main points raised there.

For example:
2.1. Whether graphical methods are in some way “less principled” than other methods of analysis.
2.2. Whether confounding bias can only decrease by conditioning on a new covariate.
2.3 Whether the M-bias, when it occurs, is merely a mathematical curiosity, unworthy of researchers attention.
2.4. Whether Bayesianism instructs us to condition on all available measurements.

If you feel strongly about defending any of these claims, (which seem to be still simmering in certain circles, see video

the Causality-Blog can be an effective arena for airing them in an open discussion.
Requests for anonymity will be honored.

3.  Forbes Magazine ran an issue on artificial Intelligence last week, to which I contributed a popular article on progress in causal analysis (from my humble perspective, of course).Comments are welcome.

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