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This chapter presents a thorough, methodologically sound analysis of experimental design and causal inference, clarifying their key roles in empirical research across scientific fields. It meticulously explains the concepts that enable researchers to make legitimate causal claims, including counterfactual thinking, randomization, control conditions, replication, and blinding. Particular attention is given to threats to internal and external validity and the analytical techniques used to mitigate them, such as analysis of covariance, instrumental variables, and propensity score matching. The chapter links abstract causal frameworks with practical research design through theoretical explanation and applied examples, thus enhancing scientific investigation’s accuracy, replicability, and ethical integrity.

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Experimental Design and Causal Inference

  • 章节

  • 发表日期：

    2025年

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  • Amjad Almusaed,
  • Asaad Almssad,
  • Ibrahim Yitmen

摘要

This chapter presents a thorough, methodologically sound analysis of experimental design and causal inference, clarifying their key roles in empirical research across scientific fields. It meticulously explains the concepts that enable researchers to make legitimate causal claims, including counterfactual thinking, randomization, control conditions, replication, and blinding. Particular attention is given to threats to internal and external validity and the analytical techniques used to mitigate them, such as analysis of covariance, instrumental variables, and propensity score matching. The chapter links abstract causal frameworks with practical research design through theoretical explanation and applied examples, thus enhancing scientific investigation’s accuracy, replicability, and ethical integrity.