[gov3009-l] Applied Statistics Workshop: Cassandra Wolos Pattanayak on Wed., Nov. 14

Konstantin Kashin kkashin at fas.harvard.edu
Sun Nov 11 22:00:23 EST 2012


Hi all,

We hope you can join us this Wednesday, November 14, 2012 for the Applied
Statistics Workshop. Cassandra Wolos
Pattanayak<http://www.people.fas.harvard.edu/~wolos/Site/Home.html>,
a College Fellow from the Department of Statistics at Harvard University,
will give a presentation entitled "A Potential Outcomes, and Typically More
Powerful, Alternative to 'Cochran-Mantel-Haenszel'". A light lunch will be
served at 12 pm and the talk will begin at 12.15.

Abstract:

> In studies of public health, outcome measures such as the odds ratio, rate
> ratio, or efficacy are often estimated across strata to assess the overall
> effect of active treatment versus control treatment. Patients may be
> partitioned into such strata or blocks by experimental design, or, in
> non-randomized studies, patients may be partitioned into subclasses based
> on key covariates or estimated propensity scores to improve observed
> covariate balance across treatment groups. In finite samples, there exist
> tests and intervals for these estimands that can be more powerful than
> tests and intervals created with Cochran-Mantel-Haenszel or analogous
> procedures . The proposed methods multiply impute missing potential
> outcomes within the Rubin Causal Model so that estimands can be directly
> estimated. The assumptions underlying these typically more powerful methods
> are appropriate in many circumstances, especially when the strata are based
> on covariates highly predictive of treatment decisions and outcomes. When
> used to draw inferences about a population from which the patients in the
> study are considered a random sample, and the sample is large, these
> methods are extremely similar to the classical methods. The proposed
> approach is particularly relevant when assessing the safety of a new
> treatment relative to a standard one because, under typical conditions, the
> tests are more powerful and the intervals are shorter, thereby detecting
> smaller differences.


An up-to-date schedule for the workshop is available at
http://www.iq.harvard.edu/events/node/1208.


Best,
Konstantin


-- 
Konstantin Kashin
Ph.D. Candidate in Government
Harvard University

Mobile: 978-844-0538
E-mail: kkashin at fas.harvard.edu
Site: http://www.konstantinkashin.com/<http://people.fas.harvard.edu/%7Ekkashin/>
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