Course Content

Below is a description of topics that will be covered during the Research Staff Training.

Topics will be covered through a combination of lectures, small group discussions, and facilitated workshops. Throughout the week, participants will have the opportunity to work and build relationships with other research staff working on randomized evaluations from a variety of organizations.

Inclusive Language

This session will provide participants with tools for integrating inclusive and asset-based language throughout the research cycle. These tools can help increase both the accuracy and credibility of a study and its findings.  

Project Management

This session will use real world examples to provide tools and resources for effective project management. 

Research Ethics and IRB

This session will provide a brief overview of the fundamental principles of research ethics, grounded in the Belmont Report’s core principles--respect for persons, beneficence, and justice. It will also discuss why and when IRB review is necessary and detail the steps/requirements for obtaining IRB approval and remaining compliant throughout the course of your study.

Measurement

This session will discuss fundamental concepts of measurement, sources of data, common forms of measurement error/bias, and best practices for data collection and survey creation.

Experimental Design Options

This session will cover key design considerations for randomized controlled trials, including choosing the unit of analysis, level of randomization, and the number and type of treatment arms. Topics include covariate balance, stratification, and cluster randomization.

This session and the accompanying Randomization and Power lab will be based on a J-PAL RCT that evaluated two programs that intend to increase learning among primary school children in India. Please read the evaluation summary before this session. It is also recommended that participants skim through the accompanying paper.

Power Theory and Calculations

This session will review statistical power and how power calculations can be used to inform decisions about sample size, treatment allocation ratios, clustering, and other critical design decisions.

This session assumes a basic understanding of power. Participants are expected to watch the RCT 101x  'Mechanics of Power Calculations' lecture from before this session.

Coding Best Practices

This session will present best practices for reproducible file organization, coding, data-handling and data validation. It will discuss methods of de-identifying data and requirements for data sharing and publication.

Strengths of Different Programming Languages  

This session will provide a high level overview of the different programming languages (Stata, R, Python) and discuss the strengths and drawbacks of each. This session also highlights the use of AI LLMs in the research process as an RA.

Git and Github

This session will highlight the importance of version control and give hands on practice with Git and GitHub.

Reporting Research Findings  

This session will focus on how to more seamlessly report internal results in a research lab led by a PI. Participants will learn how to write clear, concise, and direct reports on your work for PIs, other RAs, and your future self. 

Data Visualization

The session will focus on applying principles of design relevant to data visualization and result presentation for researchers based on Schwabish (2014). The session will include hands-on practice with tools available in statistical and word processing software.