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This study introduces practical guidelines and software for dynamical systems models, expanding beyond linear theories to include nonlinear change functions for social and behavioral scientists.

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Area of Science:

  • Social and Behavioral Sciences
  • Complex Systems Modeling

Background:

  • Dynamical systems are crucial for understanding time-evolving variables.
  • Current applications in social sciences predominantly use linear change theories.
  • There's a need for broader modeling approaches to capture complex behavioral dynamics.

Purpose of the Study:

  • To provide practical guidelines for exploring and fitting dynamical systems models.
  • To extend modeling capabilities to include nonlinear change functions.
  • To illustrate applications with examples and discuss challenges.

Main Methods:

  • Development of practical guidelines and recommendations.
  • Provision of software code for model exploration and fitting.
  • Application of methods to four illustrative examples.

Main Results:

  • Demonstration of fitting dynamical systems models with both linear and nonlinear change functions.
  • Exploration of the utility of extended modeling techniques in social and behavioral contexts.
  • Identification of practical considerations and challenges in model application.

Conclusions:

  • Dynamical systems modeling can be enhanced by incorporating nonlinear change functions.
  • The provided guidelines and code facilitate broader application of these techniques.
  • Further research is needed to address unresolved issues in complex dynamical systems analysis.