Simulation-Assisted Trend Research
Simulation-assisted trend research combines repeated cross-sectional survey data collected at multiple time points with computational simulation techniques — such as Monte Carlo methods or agent-based modeling — to project, validate, and stress-test observed trends. It extends classic trend research by replacing or supplementing extrapolation with probabilistic scenario modeling, allowing researchers to quantify uncertainty around trend trajectories and explore counterfactual futures under varying assumptions.
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- Creswell, J. W., & Creswell, J. D. (2023). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (6th ed.). SAGE Publications. · ISBN 978-1071817971
- Mooney, C. Z. (1997). Monte Carlo Simulation. SAGE Publications. (Quantitative Applications in the Social Sciences, No. 116). · ISBN 978-0803959435
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