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Integrating Open Science Principles into Quasi-Experimental Social Science Research. EdWorkingPaper No. 24-1096

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Title: Integrating Open Science Principles into Quasi-Experimental Social Science Research. EdWorkingPaper No. 24-1096
Language: English
Authors: Blake H. Heller (ORCID 0000-0003-2093-8170), Carly D. Robinson (ORCID 0000-0002-0663-1589), Annenberg Institute for School Reform at Brown University
Source: Annenberg Institute for School Reform at Brown University. 2024.
Availability: Annenberg Institute for School Reform at Brown University. Brown University Box 1985, Providence, RI 02912. Tel: 401-863-7990; Fax: 401-863-1290; e-mail: annenberg@brown.edu; Web site: https://annenberg.brown.edu/
Peer Reviewed: N
Page Count: 27
Publication Date: 2024
Sponsoring Agency: National Academy of Education (NAEd)
Document Type: Reports - Research
Descriptors: Social Science Research, Research Methodology, Quasiexperimental Design, Scientific Principles, Credibility, Replication (Evaluation), Bias, Statistical Inference, Causal Models, Research Projects, Hypothesis Testing
Abstract: Quasi-experimental methods are a cornerstone of applied social science, providing critical answers to causal questions that inform policy and practice. Although open science principles have influenced experimental research norms across the social sciences, these practices are rarely implemented in quasi-experimental research. In this paper, we explore how open science practices can enhance transparency, replicability, and credibility in quasi-experimental research. We discuss practical strategies to implement or adapt these practices for quasi-experimental researchers. We also emphasize the shared responsibility of external stakeholders, including data providers, journals, and funders to create the circumstances and incentives for open science practices to proliferate. We believe that all quasi-experimental work can benefit from an open science mentality, and this mindset shift will ultimately enhance the credibility, accessibility, replicability, and unbiasedness of quasi-experimental social science research.
Abstractor: As Provided
Entry Date: 2025
Accession Number: ED672410
Database: ERIC
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  Data: <searchLink fieldCode="AR" term="%22Blake+H%2E+Heller%22">Blake H. Heller</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2093-8170">0000-0003-2093-8170</externalLink>)<br /><searchLink fieldCode="AR" term="%22Carly+D%2E+Robinson%22">Carly D. Robinson</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-0663-1589">0000-0002-0663-1589</externalLink>)<br /><searchLink fieldCode="AR" term="%22Annenberg+Institute+for+School+Reform+at+Brown+University%22">Annenberg Institute for School Reform at Brown University</searchLink>
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  Data: Annenberg Institute for School Reform at Brown University. Brown University Box 1985, Providence, RI 02912. Tel: 401-863-7990; Fax: 401-863-1290; e-mail: annenberg@brown.edu; Web site: https://annenberg.brown.edu/
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  Data: Quasi-experimental methods are a cornerstone of applied social science, providing critical answers to causal questions that inform policy and practice. Although open science principles have influenced experimental research norms across the social sciences, these practices are rarely implemented in quasi-experimental research. In this paper, we explore how open science practices can enhance transparency, replicability, and credibility in quasi-experimental research. We discuss practical strategies to implement or adapt these practices for quasi-experimental researchers. We also emphasize the shared responsibility of external stakeholders, including data providers, journals, and funders to create the circumstances and incentives for open science practices to proliferate. We believe that all quasi-experimental work can benefit from an open science mentality, and this mindset shift will ultimately enhance the credibility, accessibility, replicability, and unbiasedness of quasi-experimental social science research.
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      – Text: English
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      – SubjectFull: Social Science Research
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      – SubjectFull: Research Methodology
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      – SubjectFull: Quasiexperimental Design
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      – SubjectFull: Scientific Principles
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      – SubjectFull: Bias
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      – SubjectFull: Statistical Inference
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      – SubjectFull: Causal Models
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      – SubjectFull: Research Projects
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      – SubjectFull: Hypothesis Testing
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              Y: 2024
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