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Simulation-Assisted Causal-Comparative Research

Simulation-assisted causal-comparative research is a hybrid observational design that combines the ex post facto logic of causal-comparative studies — comparing groups that differ on a naturally occurring variable — with computational simulation to strengthen causal inference, test counterfactuals, and assess the robustness of observed group differences. By augmenting real-world comparisons with simulated scenarios, researchers can explore causal mechanisms that cannot be manipulated experimentally.

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Sources

  1. Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to Design and Evaluate Research in Education (10th ed.). McGraw-Hill. ISBN: 978-1260087352
  2. Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 978-0136062127

Related methods

ScholarGateSimulation-assisted causal-comparative research (Simulation-Assisted Causal-Comparative Research Design). Retrieved 2026-06-04 from https://scholargate.app/en/research-design/simulation-assisted-causal-comparative-research