System dynamics models are often constructed to improve system performance by identifying and modifying feedback mechanisms that drive system behavior. Once identified, these feedback mechanisms can be used to design and test policies for system performance improvement. A preliminary step in developing policies is the identification of high leverage parameters and structures, the influential model sections that drive system behavior. The current work clarifies and extends the use of statistical screening (Ford and Flynn, 2005) as a model analysis tool with a six step process that identifies specific model sections for further analysis and development. The work also presents a method that clarifies the results of model analysis with statistical screening to practicing managers Statistical screening offers system dynamicists a user-friendly tool that can be used to help explain how model structure drives system behavior.

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Date created

• 2007 July 29-2007 August 2

Type

• Document

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• Processing documentation available at: https://wiki.albany.edu/display/SCA/Processing+Ingested+Digital+Files

License

• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International

  
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ITEM CONTEXT

Part of

298eed5a7fe199ac661be72f3a39f134

Scope and Contents

Part of

0619e689ce89476bfd3b88323c5a9410

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Part of

23d738ba88f8333bc39725f9cb5bd0b8

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Collection

System Dynamic Society Records

Scope and Contents

Collecting area

• This collection is part of the University Archives