Abstract
Instrumental variable (IV) analysis is a statistical approach that enables valid estimation of causal effects, even in non-experimental settings where randomization is not possible. Despite its potential utility, IV analysis remains underutilized in Korean education research. The purpose of this paper is to introduce the fundamental principles of IV analysis and its applications. Specifically, the paper employs causal graphs to provide a more intuitive explanation of the key assumptions and mechanism underlying IV analysis. In addition to providing theoretical explanations, the paper explores the applicability of IV analysis in the context of education research through examining randomized encouragement designs, perceived construct studies, and treatment noncompliance. By doing so, this paper aims to facilitate a better understanding of theoretical foundations and practical considerations when applying IV analysis in education research.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
