Our library of practical resources is intended for researchers and research staff undertaking randomized evaluations, as well as those teaching the technique to others, and anyone interested in how randomized evaluations are conducted.
Incorporating lessons learned through our own experience and through guidance from researchers and research organizations, we provide practical advice for designing, implementing, and communicating about evaluations. These resources are a collaborative effort. We credit the authors of all the resources we post here, and link to their original work wherever possible.
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Introduction to Randomized Evaluations
A non-technical overview and step-by-step introduction for those who are new to randomized evaluations, as well as case studies and other teaching resources.
Before Starting a Project
Tips on successful field management and implementation partnerships for researchers who are new to fieldwork.
Highlights include: annotated checklist for designing an informed consent process, detailed advice on grant proposals and budgeting, and suggestions for proactive measures to help ensure ethical principles are followed in research design and implementation.
Data Collection and Access
This section contains guidance specific to working with surveyors or survey companies, information about administrative data collection, and information applicable to all modes of data collection, such as on data security, data quality, and grant management.
Processing and Analysis
All the steps in a research project after the data was collected or assembled, from data cleaning to communicating results.
Drawing on evidence and examples from literature on mail experiments and mail surveys, this resource suggests strategies for increasing responses to mail surveys and mailings targeted at a fixed pool...
This resource outlines steps to establish and build a strong working relationship with an implementing partner at the beginning of a randomized evaluation. Topics include questions to consider when...
The goal of measurement is to get reliable data with which to answer research questions and assess theories of change. Inaccurate measurement can lead to unreliable data, from which it is difficult to...