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البحث المقطعي بمساعدة المحاكاة×محاكاة مونت كارلو×
المجالتصميم البحثاتخاذ القرار
العائلةProcess / pipelineMCDM
سنة النشأة2000s–2010s (consolidated as a named hybrid approach)1949
صاحب الطريقةEmerged 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.
النوعQuantitative hybrid research designRobustness wrapper — Monte Carlo uncertainty propagation
المصدر التأسيسيPearce, 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 ↗
الأسماء البديلةsimulation-enhanced cross-sectional study, hybrid simulation cross-sectional design, cross-sectional simulation study, SACSR
ذات صلة30
الملخصSimulation-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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ScholarGateقارن الطرق: Simulation-assisted cross-sectional research · MONTE-CARLO-SIMULATION. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare