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模拟辅助趋势研究×面板研究×
领域研究设计研究设计
方法族Process / pipelineProcess / pipeline
起源年份1990s–2000s (convergence of computational simulation with survey-based trend designs)1970s-1980s (econometric formalization); earlier social survey use from 1940s
提出者Synthesized from trend research (Creswell) and Monte Carlo / agent-based simulation traditions (Mooney, 1997)Social science and econometric traditions; systematized by Cheng Hsiao and others from the 1970s-1980s
类型Quantitative research design with computational augmentationQuantitative longitudinal observational design
开创性文献Creswell, J. W., & Creswell, J. D. (2023). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (6th ed.). SAGE Publications. ISBN: 978-1071817971Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717
别名simulation-augmented trend study, Monte Carlo trend research, computational trend analysis, simulation-based longitudinal trend designpanel study, panel survey, longitudinal panel, repeated-measures panel
相关43
摘要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.Panel research is a quantitative longitudinal design in which the same individuals, organizations, or other units are measured repeatedly across two or more time points. Unlike cross-sectional surveys that capture a single snapshot, a panel tracks change within units, enabling researchers to separate genuine within-unit change from between-unit differences and to model causal dynamics over time.
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ScholarGate方法对比: Simulation-Assisted Trend Research · Panel Research. 于 2026-06-18 检索自 https://scholargate.app/zh/compare