Useful Links and Resources
Preregistration, Pre-Analysis Plans (PAPs), and Registered Reports (RRs)
A Template for Registered Reports (OSF)
Follow this link to access a Registered Report (RR) template on the Open Science Framework (OSF). This template walks researchers through key components of a Stage 1 Registered Report, including research questions, hypotheses, sampling plans, and analysis strategies, ensuring a structured and transparent research process.
Practical recommendations for RR publication format (Trends in Neurosciences)
Follow this link to explore a research article titled “Practical Considerations for Navigating Registered Reports,” published in Trends in Neurosciences. The article discusses how Registered Reports combine peer review with best practices in hypothesis-driven research and offers valuable recommendations for researchers using this format.
Research Design in the Social Sciences Book and DeclareDesign Package
DeclareDesign Package
Follow this link to explore DeclareDesign, a platform for developing and assessing research designs before data collection. The project introduces the MIDA framework, where a design is characterized by four elements: a Model, an Inquiry, a Data strategy, and an Answer strategy. This structure helps researchers make explicit, transparent choices throughout the research process. By declaring each element in code and using simulations, researchers can diagnose and improve their designs before implementation.
Research Design in the Social Sciences Book
Follow this link to access the official book for DeclareDesign. The book provides a comprehensive guide to the MIDA framework, introducing design as an object that can be declared, diagnosed, and redesigned. It offers both conceptual foundations and practical tools, including a design library with code examples for a wide range of empirical strategies. Written for students, applied researchers, and decision-makers alike, the book emphasizes clear thinking about research goals and how data and analysis strategies align with those goals—without requiring a background in statistics or coding
Example Pre-analysis Plans and Registered Reports
PAPs & Preregistrations:
Banerjee, S., & Picard, J.Thinking through norms can make them more effective. Experimental evidence on reflective climate policies in the UK.Journal of Behavioral and Experimental Economics106, 102024.Pre-analysis Plan
Fossen, F. M., Neyse, L., & Schroeder, C.Does Cognitive Reflection Relate to Preferences and Socio-Economic Outcomes?Available at SSRN 4599840. (Forthcoming in JPE Microeconomics).Pre-analysis Plan
Registered Reports:
Ioannidis, K.Anchoring on valuations and perceived informativeness.Journal of Behavioral and Experimental Economics106, 102060.Pre-analysis Plan
Applications of Reproducibility and Replicability Typology in the Literature
The list below highlights the diverse approaches to replication and reproducibility presented in the special issue “The Science and Practice of Replication in Experimental Economics” from the Journal of Economic Behavior & Organization. It classifies each paper by its replication or reproduction type, offering a clear overview of how different studies contribute to the ongoing conversation about the credibility and reliability of experimental economics. This classification helps illustrate the variety of methods being used to validate and strengthen economic research through replication.
On the Interpretation of Giving in Dictator Games When the Recipient is a Charity
Journal of Economic Behavior & Organization.
Jeffrey A. LivingstonRustam Rasulmukhamedov
Classification:
Direct replicability: Similar population; Conceptual replicability: Similar population
Data:
Experimental Data
Scarcity improves economic valuations when cognitively salient
Journal of Economic Behavior & Organization.
Ozan IslerOnurcan YilmazUwe Dulleck
Classification:
Direct replicability: Similar population
Data:
Experimental Data
In addition, the list below applies the proposed typology to some recent working papers published by the Institute for Replication in their discussion paper series. These papers focus primarily on testing the reproducibility of studies from top economics, political science and psychology journals. By classifying these studies according to the typology, it is possible to gain a clearer understanding of how replication efforts are being carried out in different research contexts and how they contribute to enhancing the reliability of findings in social science.
Replicating Backfire Effects in Anti-Corruption Messaging: A Comment on Cheeseman and Peiffer (2022)
I4R Discussion Paper Series No. 94.
Bergeron-Boutin, OlivierCiobanu, CostinCohen, GuilaErlich, Aaron
Classification:
Computational reproducibility Robustness reproducibility
Data:
Experimental Data
Replicating "Run-off elections in the laboratory"
I4R Discussion Paper Series No. 99.
Hausladen, Carina I.Hu, Shiang-HungLevin, Joel M.
Classification:
Computational reproducibility
Data:
Experimental Data