Improving model understanding using statistical screening

Timothy R.B. Taylor, David N. Ford, Andrew Ford

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

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 as a tool to improve model understanding, explanation, and development with a six-step process. Statistical screening adds rigor to model analysis by objectively identifying high-leverage model parameters and structures for further analysis. Statistical screening offers system dynamicists a user-friendly tool that can be used to help explain how model structure drives behavior.

Original languageEnglish
Pages (from-to)73-87
Number of pages15
JournalSystem Dynamics Review
Volume26
Issue number1
DOIs
StatePublished - Jan 2010

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Strategy and Management
  • Management of Technology and Innovation

Fingerprint

Dive into the research topics of 'Improving model understanding using statistical screening'. Together they form a unique fingerprint.

Cite this