Both IPA and CEGA aim to support high quality, transparent, reproducible research. The research support staff at both organizations are typically tasked with preparing data and code for publication. However, key steps for preparing data and code take place as early as the study design phase as well as in the data collection process.
We have several objectives for this workshop:
- Familiarize participants with the importance of reproducible research and research transparency (both for their own work as well as from a public good perspective).
- Present concrete guidance and tools e.g. recommendations from IPA’s best practice manual for managing data/code, BITSS’ reproducible research handbook, Github, Open Science Framework and Dataverse.
- Provide an excellent setting with support for participants to practice new skills / tools, and to improve their own data/code from their projects.
Given this is a pilot, IPA and BITSS will send targeted invitations for up to 30 participants who meet the following criteria:
- Master’s level (either completed, or ongoing) or higher in economics, public policy, statistics, or other relevant degree
- Training and experience with statistics
- Experience with and currently using STATA and/or R for their own research
Date and Time
Mar 7, 2016 — Mar 8, 2016