{"title":"Defining, identifying, and estimating causal effects with the potential outcomes framework: a review for education research","authors":"Bryan Keller, Zach Branson","doi":"10.1007/s12564-024-09957-2","DOIUrl":null,"url":null,"abstract":"<div><p>Causal inference involves determining whether a treatment (e.g., an education program) causes a change in outcomes (e.g., academic achievement). It is well-known that causal effects are more challenging to estimate than associations. Over the past 50 years, the potential outcomes framework has become one of the most widely used approaches for defining, identifying, and estimating causal effects. In this paper, we review the potential outcomes framework with a focus on potential outcomes notation to define individual and average causal effects. We then show how three canonical assumptions, Unconfoundedness, Positivity, and Consistency, may be used to identify average causal effects. The identification results motivate methods for estimating causal effects in practice, which include model-based estimators, such as regression, inverse probability weighting, and doubly robust estimation, and procedures that target covariate balance, such as matching and stratification. Examples and discussion are grounded in the context of a running example of a study aimed at assessing the causal effect of receipt of special education services on 5th grade mathematics achievement in school-aged children. Practical considerations for education research are discussed.</p></div>","PeriodicalId":47344,"journal":{"name":"Asia Pacific Education Review","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asia Pacific Education Review","FirstCategoryId":"95","ListUrlMain":"https://link.springer.com/article/10.1007/s12564-024-09957-2","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0
Abstract
Causal inference involves determining whether a treatment (e.g., an education program) causes a change in outcomes (e.g., academic achievement). It is well-known that causal effects are more challenging to estimate than associations. Over the past 50 years, the potential outcomes framework has become one of the most widely used approaches for defining, identifying, and estimating causal effects. In this paper, we review the potential outcomes framework with a focus on potential outcomes notation to define individual and average causal effects. We then show how three canonical assumptions, Unconfoundedness, Positivity, and Consistency, may be used to identify average causal effects. The identification results motivate methods for estimating causal effects in practice, which include model-based estimators, such as regression, inverse probability weighting, and doubly robust estimation, and procedures that target covariate balance, such as matching and stratification. Examples and discussion are grounded in the context of a running example of a study aimed at assessing the causal effect of receipt of special education services on 5th grade mathematics achievement in school-aged children. Practical considerations for education research are discussed.
期刊介绍:
The Asia Pacific Education Review (APER) aims to stimulate research, encourage academic exchange, and enhance the professional development of scholars and other researchers who are interested in educational and cultural issues in the Asia Pacific region. APER covers all areas of educational research, with a focus on cross-cultural, comparative and other studies with a broad Asia-Pacific context.
APER is a peer reviewed journal produced by the Education Research Institute at Seoul National University. It was founded by the Institute of Asia Pacific Education Development, Seoul National University in 2000, which is owned and operated by Education Research Institute at Seoul National University since 2003.
APER requires all submitted manuscripts to follow the seventh edition of the Publication Manual of the American Psychological Association (APA; http://www.apastyle.org/index.aspx).