Salīdzināt metodes

	Simulācijas atbalstīts ex post facto pētījuma dizains	Monte Carlo simulācija
Nozare	Pētījuma dizains	Lēmumu pieņemšana
Saime	Process / pipeline	MCDM
Izcelsmes gads	Ex post facto: 1964; simulation-assisted hybrid: 1990s–2000s	1949
Autors	Kerlinger, F. N. (ex post facto basis); simulation integration drawn from computational social science (Axelrod, Epstein, 1990s)	Metropolis, N., Ulam, S.
Tips	Non-experimental observational design with computational augmentation	Robustness wrapper — Monte Carlo uncertainty propagation
Pirmavots	Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston.	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Citi nosaukumi	simulation-enhanced causal-comparative design, ex post facto with simulation, retrospective simulation design, SAEPF design	—
Saistītās	4	0
Kopsavilkums	Simulation-assisted ex post facto design is a non-experimental observational approach in which the researcher examines already-occurred events or conditions using existing records and then supplements the empirical analysis with computational simulation to approximate counterfactual scenarios that cannot be observed in reality. The design retains the retrospective, naturalistic character of classic ex post facto research while leveraging agent-based, Monte Carlo, or system-dynamics simulation to address the inherent confound limitations of purely archival work.	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.