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Computing Statistical Power for the Difference in Differences Design

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Title: Computing Statistical Power for the Difference in Differences Design
Language: English
Authors: E. C. Hedberg (ORCID 0000-0003-0679-0720), Larry V. Hedges
Source: Evaluation Review. 2026 50(1):149-180.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 32
Publication Date: 2026
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R305D200045
Document Type: Journal Articles
Reports - Research
Descriptors: Statistical Analysis, Computation, Effect Size, Quasiexperimental Design, Regression (Statistics), Intervention, Pretests Posttests
DOI: 10.1177/0193841X251380898
ISSN: 0193-841X
1552-3926
Abstract: The difference in differences design is widely used to assess treatment effects in natural experiments or other situations where random assignment cannot, or is not, used (see, e.g., Angrist & Pischke, 2009). The researcher must make important decisions about which comparisons to make, the measurements to make, and perhaps the number of individuals whose data is included in each timepoint. Also, interpretation of any statistical results, particularly null results, is improved by understanding the sensitivity of the design. This paper describes methods for computing the statistical power for tests of treatment effects in the difference in differences design. We describe alternative approaches to the analysis of the design, show which are equivalent, and provide expressions for computing statistical power and determining minimum detectable effect sizes. We then discuss how these methods could be generalized to unbalanced designs, designs with covariates, and designs more than two timepoints including difference in difference in differences designs.
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2026
Accession Number: EJ1492013
Database: ERIC
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  Data: The difference in differences design is widely used to assess treatment effects in natural experiments or other situations where random assignment cannot, or is not, used (see, e.g., Angrist & Pischke, 2009). The researcher must make important decisions about which comparisons to make, the measurements to make, and perhaps the number of individuals whose data is included in each timepoint. Also, interpretation of any statistical results, particularly null results, is improved by understanding the sensitivity of the design. This paper describes methods for computing the statistical power for tests of treatment effects in the difference in differences design. We describe alternative approaches to the analysis of the design, show which are equivalent, and provide expressions for computing statistical power and determining minimum detectable effect sizes. We then discuss how these methods could be generalized to unbalanced designs, designs with covariates, and designs more than two timepoints including difference in difference in differences designs.
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        Value: 10.1177/0193841X251380898
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        PageCount: 32
        StartPage: 149
    Subjects:
      – SubjectFull: Statistical Analysis
        Type: general
      – SubjectFull: Computation
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      – SubjectFull: Effect Size
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      – SubjectFull: Quasiexperimental Design
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      – SubjectFull: Regression (Statistics)
        Type: general
      – SubjectFull: Intervention
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      – SubjectFull: Pretests Posttests
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      – TitleFull: Computing Statistical Power for the Difference in Differences Design
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              Y: 2026
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