Abstract #300169

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

Back to main JSM 2002 Program page
JSM 2002 Abstract #300169
Activity Number: 293
Type: Invited
Date/Time: Wednesday, August 14, 2002 : 10:30 AM to 12:20 PM
Sponsor: Section on Health Policy Statistics*
Abstract - #300169
Title: Measuring Uncertainty in Complex Decision Models
Author(s): Giovanni Parmigiani*+
Affiliation(s): Johns Hopkins University
Address: 550 N. Broadway, Suite 1103, Baltimore, Maryland, 21205, USA
Keywords: Decision modeling ; Bayesian decision theory ; sensitivity analysis ; simulation ; stroke ; health policy
Abstract:

Simulation models used in support of health policy and clinical decision making often consider the course of a disease over a long period of time and draw evidence from a broad knowledge base, including epidemiological cohort and case control studies, randomized clinical trials, expert opinions, and more. These models are termed "complex decision models." The presentation is a brief introduction to complex decision models, their relation to Bayesian decision theory, and the statistical modelling tools typically used to capture the various sources of uncertainty. A special emphasis will be placed on implementation and interpretation of scenario--based and probabilistic sensitivity analysis.

  • The address information is for the authors that have a + after their name.
  • Authors who are presenting talks have a * after their name.

Back to the full JSM 2002 program

JSM 2002

For information, contact meetings@amstat.org or phone (703) 684-1221.

If you have questions about the Continuing Education program, please contact the Education Department.

Revised March 2002