Causal Inference in

        Statistics and the
        Quantitative Sciences

            3-8 May, 2009 at the
            Banff International Research Station


Causal inference attempts to uncover the structure of the data and eliminate all non-causative explanations for an observed association. The goal of most, if not all, statistical inference is to uncover causal relationships. However it is not in general possible to conclude causality from a standard statistical inference procedure, it is merely possible to conclude that the observed association between two variables is not due to chance. Statistical inference procedures do not provide any information about which variable causes the other, or whether the apparent relationship between the two variables is due to another, confounding variable. The explicit study of causation was first introduced into the statistical sciences in 1986 by Paul Holland. Since then, there has been an explosion of research into the area in a variety of disciplines including statistics (particularly biostatistics), computer science, and economics. Despite this, there is relatively little research into causal inference in Canada.

The purpose of this inter-disciplinary workshop is threefold: First, to review recent advances in the causal inferences in statistic; Secondly, to bring together researchers from related fields, in particular Economics and Computer Sciences, who work on causal inference methodology so that we may share approaches and knowledge; and finally, to increase the profile of causal inference amongst statisticians in Canada.

The overall theme of the workshop is causal inference in statistics. Each of the five days of the workshop will focus on a particular sub-theme. In particular, talks and discussions will concentrate on
1.    Inference and asymptotic theory
2.    Balancing scores and inverse weighting: advances in biostatistics
3.    Instrumental variables and structural equation models: connecting statistics and econometrics
4.    Adaptive treatment regimes: connecting statistics and computer science
5.    Bayesian causal inference: connecting disciplines within statistics


Organizers: Erica E. M. Moodie and David A. Stephens, McGill University


BIRS Site
(Including participant list and video & audio recordings)


Schedule & Abstracts

Proceedings: Special Issue of the
International Journal of Biostatistics


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Accommodation:
Participants of BIRS programmes are housed in Corbett Hall at the Banff Centre. There is a separate bedroom for each participant; most rooms share a bathroom with one other participant. Each room has a queen size bed, dresser, desk and a computer terminal.
Participants are expected to arrive on Sunday afternoon (check-in after 4 p.m.) and to depart Friday midday (checkout at noon). Accommodation and meals are provided for participants for this period. Information about the BIRS guest policy is available here.
Alternatively, accommodation is available (at participants' expense) in the town of Banff, about a 10 minute walk from the Banff Centre.

Banff:
The nearest international airport is Calgary, Alberta, Canada. There is a regular shuttle
service from the airport to the Banff Centre. Travel information can be found here.