DIME Analytics supports quality research processes across the DIME portfolio, offers public trainings, and develops tools for the global community of development researchers. DIME Analytics’ primary portfolio includes: the DIME Wiki, a one-stop shop for practical guidance and resources on impact evaluation research and the accompanying guidebook Data for Development Impact; ietoolkit and iefieldkit, Stata code packages featuring commands to routinize common impact evaluation tasks; and Manage Successful Impact Evaluations, our flagship training designed to improve the skills and knowledge of impact evaluation practitioners.
DIME Analytics creates tools that improve the quality of impact evaluation research for all. We take advantage of the concentration and scale of research at DIME to develop and test solutions to ensure high quality of data collection and research quality across our portfolio, and to make public training and tools available to the larger community of development researchers who might not have the same capabilities.
Public Resources and Training
- Manage Successful Impact Evaluations
DIME Analytics’ flagship training is a week-long annual course, open to the public (2019 course materials). The 2020 course has been postponed due to the COVID-19 crisis. In the meantime, we will hold a virtual Manage Successful Surveys course in July.
- DIME Wiki
One-stop shop for impact evaluation research solutions
- Data for Development Impact
A new technical handbook: how to make data work efficient, ethical, transparent, and scalable. This practical guide provides code examples and links to the DIME Wiki and other research resources.
- IE Summer School
A week-long course for graduate students in partnership with the University of Rwanda, covering the theoretical underpinnings of causal inference and offering hands-on tutorials on data analysis and survey design.
- Software training (Stata, GitHub, LaTeX)
Trainings for World Bank staff and government counterparts on common software for impact evaluation research, all publicly available on GitHub.
- Computational Reproducibility
DIME Analytics checks “computational reproducibility” for all DIME publications, verifying that all tables and figures are exactly reproducible from the provided code. Analytics also provides technical support with data and code publication and assists in creating replication packages.
DIME Analytics offers computational reproducibility checks to all World Bank researchers, contact firstname.lastname@example.org for details.
- Reproducible Research Agenda
Regular events and trainings to promote reproducible research, in collaboration with the Berkeley Institute for Transparency in Social Science (BITSS) and other partners. Events in 2019 included Making Analytics Reusable (event, blog) and Transparency, Reproducibility and Credibility: a Research Symposium (event, presentations, blog).
Quality Assurance for Data Collection
- SurveyCTO Platform
Management of the World Bank’s SurveyCTO platform for electronic data collection, and organized trainings on the tool.
- Survey Review
Open source resources for data collection (e.g. checklists), and technical support to all DIME teams preparing for data collection.
- Measurement Conference
Annual conference on data and measurement innovations in partnership with the Center for Effective Global Action (CEGA). The 2020 topic is Data Integration and Data Fusion.
2019: Crisis Preparedness and Response | 2018: Artificial Intelligence and Economic Development | blog
Open Source Research Tools
Take advantage of scope and scale of DIME research to develop and test econometric and technical solutions and develop public tools.