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The generic modeling fallacy: Average biomechanical models often produce non-average results!

Douglas D Cook1, Daniel J Robertson1

  • 1Division of Engineering, New York University - Abu Dhabi, Abu Dhabi, United Arab Emirates.

Journal of Biomechanics
|October 25, 2016
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Summary

Computational biomechanics models using average parameters do not yield average population results. Non-average parameters can produce average behaviors, revealing the "Generic Modeling Fallacy".

Keywords:
AverageBiomechanicsFallacyGenericModel

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Area of Science:

  • Computational Biomechanics
  • Mathematical Modeling

Background:

  • Computational biomechanics models often use average input parameters, assuming representative population outcomes.
  • This assumption is prevalent in research and clinical applications.

Purpose of the Study:

  • To investigate the validity of using average input parameters in computational biomechanics models.
  • To identify and explain discrepancies between average model behavior and population averages.

Main Methods:

  • Stochastic Monte Carlo analysis was performed on two common biomechanical models.
  • Input parameters were varied to assess their impact on model output.

Main Results:

  • Consistent discrepancies were observed between average models and the average behavior of the population.
  • Models with non-average, broadly distributed input parameters often produced average or near-average results.
  • Average models did not produce average population behaviors; models producing average behaviors had non-average parameters.

Conclusions:

  • The study identifies and names the "Generic Modeling Fallacy": average models do not yield average population results.
  • Findings challenge the common practice of using average input parameters in computational modeling.
  • Suggestions for avoiding the Generic Modeling Fallacy and mathematical explanations are provided.