So sánh phương pháp

	Nghiên cứu xu hướng có hỗ trợ mô phỏng	Nghiên cứu bảng
Lĩnh vực	Thiết kế nghiên cứu	Thiết kế nghiên cứu
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1990s–2000s (convergence of computational simulation with survey-based trend designs)	1970s-1980s (econometric formalization); earlier social survey use from 1940s
Người khởi xướng	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
Loại	Quantitative research design with computational augmentation	Quantitative longitudinal observational design
Công trình gốc	Creswell, J. W., & Creswell, J. D. (2023). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (6th ed.). SAGE Publications. ISBN: 978-1071817971	Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717
Tên gọi khác	simulation-augmented trend study, Monte Carlo trend research, computational trend analysis, simulation-based longitudinal trend design	panel study, panel survey, longitudinal panel, repeated-measures panel
Liên quan	4	3
Tóm tắt	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.