## Donald Rubin - PRIMES Distinguished Lecture Series 
   Thursday January 19th, 5.pm., CSU-Fort Collins 
   Reception before - dinner afterwards

PRIMES Distinguished Lecture 

"Causal Inference Through Potential Outcomes:  
 Application to Quality of Life Studies with 'Censoring' Due to
Death and to Studies of the Effect of Job-training Programs on Wages"

(The Abstract is at the end of this note.)

Before the lecture, there will be a formal reception from 4:10 - 5 pm.
Afterwards, people from  the lecture are welcome to attend a dinner at
a nearby restaurant.  If anyone coming from  the Denver or Boulder area
is interested in car-pooling, please send a note to pocernic@ucar.edu
and we can attempt to help coordinate rides.   For those outside the
Fort Collins area, we are hoping this will be a fun opportunity to
meet some of the statistics people up at CSU. Its not required but if
you think you are interested in dinner, please let me know.  

For directions to CSU see.  (For those of you with some knowledge of
CSU's campus, the Clark Building is just east of the Morgan Library,
southeast of the Lory Student Center)

http://www.map.colostate.edu/

For more information on this and other PRIMES Events see
http://www.primes.colostate.edu/

Abstract: 

Causal inference is best understood using potential outcomes, which
include all post treatment quantities. The use of potential outcomes
to  define causal effects is particularly important in more complex
settings, i.e., observational studies or randomized experiments with
complications  such as noncompliance. Here we deal with the issue of
estimating the casual effect of a treatment on a primary outcome that
is "censored" by an  intermediate outcome, for example, the effect of
a drug treatment on Quality of Life (QOL) in a randomized experiment
where some of the  patients die before their QOL can be
assessed. Because both QOL and death are post-randomization
quantities, they both should be  considered potential outcomes, and
the effect of treatment versus control on QOL is only well-defined for
the subset of patients who would live  under either treatment or
control. Another application is to an educational program designed to
increase final test scores, which are not defined  for those who drop
out of school before taking the test. A further application is to
studies of the effect of job-training programs on wages, where 
wages are only defined for those who are employed, and thus the effect
of the job-training program on wages is only well-defined for the
subset of individuals who would be employed whether or not they were
trained. Some empirical results are presented from Zhang, Rubin and
Mealli (2004),  which indicate that this framework can lead to new
insights because the analysis is not predicated on traditional econometric
assumptions. 

-- Matt Pocernich National Center for Atmospheric Research Research Applications Laboratory (303) 497-8312 _______________________________________________ Cowystats mailing list Cowystats@ucar.edu http://mailman.ucar.edu/mailman/listinfo/cowystats