Statistical screening of system dynamics models

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Abstract
This paper describes a pragmatic method of searching for the key inputs to a system dynamics model. This analysis is known as screening. The goal is to learn which of the many uncertain inputs stand out as most influential. The method is implemented with readily available software and relies on the simple correlation coefficient to indicate the relative importance of model inputs at different times in the simulation. The screening is demonstrated with two examples with step‐by‐step instructions. The paper recommends that screening analysis be used in an iterative process of screening and model expansion to arrive at tolerance intervals on model results. The appendices compare screening analysis with analytical methods to identify the key inputs to system dynamics models. Copyright © 2005 John Wiley & Sons, Ltd.

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