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پژوهش مقطعی با کمک شبیه‌سازی×شبیه‌سازی مونت کارلو×
حوزهطراحی پژوهشتصمیم‌گیری
خانوادهProcess / pipelineMCDM
سال پیدایش2000s–2010s (consolidated as a named hybrid approach)1949
پدیدآورEmerged from epidemiology and systems science (no single originator; synthesises Pearce-type cross-sectional designs with simulation modelling traditions from Sterman and colleagues)Metropolis, N., Ulam, S.
نوعQuantitative hybrid research designRobustness wrapper — Monte Carlo uncertainty propagation
منبع بنیادینPearce, N. (2012). Classification of epidemiological study designs. International Journal of Epidemiology, 41(2), 393–397. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
نام‌های دیگرsimulation-enhanced cross-sectional study, hybrid simulation cross-sectional design, cross-sectional simulation study, SACSR
مرتبط30
خلاصهSimulation-assisted cross-sectional research combines the one-time, population-wide snapshot of a classic cross-sectional survey with computational simulation — such as agent-based modelling or Monte Carlo methods — to extend what can be inferred from data collected at a single point in time. Empirical cross-sectional data calibrate the simulation, which then explores counterfactuals, rare subgroups, or dynamic processes that the survey alone cannot reveal.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateمقایسهٔ روش‌ها: Simulation-assisted cross-sectional research · MONTE-CARLO-SIMULATION. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare