Short Course 1-day short
course by Professor Don Rubin of Harvard University
Sponsor |
San Francisco and Bay Area Chapter of ASA |
Date |
Oct. 19,
2012 (Friday) |
Venue |
Maude Fife Room (315 Wheeler
Hall) of English Department at UC Berkeley. |
Title: |
Causal inference in
experiments and observational studies using potential outcomes |
Abstract
This course begins with the careful definition of causal effects using
potential outcomes. Examples are used to clarify essential ideas, as well as to
emphasize the importance of having an assignment mechanism for treatment
indicators. Methods of inference due to Fisher(1925)
and to Neyman (1923), which only use the randomization
distribution to draw inferences, will be described. Regular assignment
mechanisms (Imbens and Rubin 2012), which are
generalized randomized experiments, are the basic template for structuring the
design and the analysis of observational studies, and such mechanisms are
essentially fully specified by the collection of propensity scores (Rosenbaum
and Rubin 1983). Their estimation and diagnostics for the balance they can
create are critical in the outcome-free design phase of observational studies,
and these activities are illustrated using real examples. Bayesian posterior
predictive inference (Rubin 1978) can be very helpful in nearly all analyses of
data for causal effects, and it too is applied to real and artificial examples.
More advanced topics, for instance ones involving principal stratification,
which is a generalization of the econometric method of instrumental variables,
is also considered and illustrated with real examples. The particular examples
chosen will be selected after receiving input from the class participants. Some
open time is reserved at the end of the day for more extensive questions.
Registration Details:
Late registration rates (which is within 3 days of the event)
ASA Member/ Statistical Society of Canada |
US$ 315.00 |
Academic - NonStudent |
US$ 315.00 |
Student |
US$ 155.00 |
Non-member |
US$ 400.00 |
Registration: https://www.123signup.com/register?id=sdhvk
Questions? Contact Lu
Tian lutian@stanford.edu
or Kit Fun Lau kitfunlau@hotmail.com
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