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
Resources
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
Resources
Tips on successful field management and implementation partnerships for researchers who are new to fieldwork.
Project Planning
Resources
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.
Research Design
Resources
Data Collection and Access
Resources
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
Resources
All the steps in a research project after the data was collected or assembled, from data cleaning to communicating results.
Survey programming
Cette ressource présente les bonnes pratiques en matière de programmation d’enquêtes à l’aide d’un logiciel d’entretien en face à face assisté par ordinateur (CAPI). Nous nous appuyons principalement...
Data quality checks
High-frequency checks, back-checks, and spot-checks can be used to detect programming errors, surveyor errors, data fabrication, poorly understood questions, and other issues. The results of these...
Contrôles de la qualité des données
Des techniques comme les contrôles à haute fréquence, les back-checks et les contrôles inopinés peuvent être utilisés pour détecter les erreurs de programmation, les erreurs commises par les...
Data cleaning and management
Although quality control checks in the field should catch most errors in data collection, there are a number of steps you will have to undertake to prepare your collected data for analysis. This...
Nettoyage et gestion des données
Bien que les opérations de contrôle de la qualité effectuées sur le terrain doivent permettre de détecter la plupart des erreurs commises lors de la collecte des données, il faudra malgré tout prendre...
Data visualization
Data visualization can be helpful at many stages of the research process, from data reporting to analysis and publication. Relative to regression tables, cross-tabs, and summary statistics, data...
Visualisation des données
Les méthodes de visualisation des données peuvent être utiles à de nombreux stades du processus de recherche, de l’établissement de rapports sur les données à l’analyse et à la publication. Cette...
Data analysis
This guide provides an overview of data analysis for randomized evaluations in order to estimate causal impact. It is intended to provide something of a starting point and orient individuals not...