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AVVISO DI SEMINARIO



A V V I S O di S E M I N A R I O

Nell’ambito del dottorato di ricerca in Statistica Economica, il
PROF. DONALD B. RUBIN
John L. Loeb Professor of Statistics, Università di Harvard

terrà un seminario dal titolo:

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

Il seminario avrà luogo:

LUNEDÌ 14 FEBBRAIO 2005
ALLE ORE 11.00 IN AULA GINI
PIANO TERRA DELLA FACOLTÀ DI SCIENZE STATISTICHE,
UNIVERSITÀ DI ROMA “LA SAPIENZA”


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.

-- 





--------------------------------
 Dr. M. Grazia Pittau
 DIP. Contabilità Nazionale e APS
 Università di Roma "La Sapienza"
 BOX 83 ROMA 62
 P.le Aldo Moro, 5
 00185 ROMA
 ITALY
 tel ++39 06 49910654
 fax ++39 06 4453246
URL http://w3.uniroma1.it/dcnaps/pittau/





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