Increasing the efficiency of Monte Carlo cohort simulations with variance reduction techniques.

Increasing the efficiency of Monte Carlo cohort simulations with variance reduction techniques. Research Abstract Details 

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Increasing the efficiency of Monte Carlo cohort simulations with variance reduction techniques. Abstract Text:

Steven M Shechter,Andrew J Schaefer,R Scott Braithwaite,Mark S Roberts,

The authors discuss techniques for Monte Carlo (MC) cohort simulations that reduce the number of simulation replications required to achieve a given degree of precision for various output measures. Known as variance reduction techniques, they are often used in industrial engineering and operations research models, but they are seldom used in medical models. However, most MC cohort simulations are well suited to the implementation of these techniques. The authors discuss the cost of implementation versus the benefit of reduced replications.

Increasing the efficiency of Monte Carlo cohort simulations with variance reduction techniques. Publishing Authors By Initials

SM Shechter,AJ Schaefer,RS Braithwaite,MS Roberts,

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Increasing the efficiency of Monte Carlo cohort simulations with variance reduction techniques. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: Medical decision making : an international journal

VOLUME: 26

Page Numbers: 550-3

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ISSN: 0272-989X

DAY: 3

MONTH: 12

YEAR: 2007

Increasing the efficiency of Monte Carlo cohort simulations with variance reduction techniques. Information

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LANGUAGE: eng

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Grant and Affiliation Information for Increasing the efficiency of Monte Carlo cohort simulations with variance reduction techniques.

AFFILIATION: Department of Industrial Engineering, University of Pittsburgh, USA. steven.shechter@sauder.ubc.edu

Country: United States

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MEDLINETA: Med Decis Making

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