Bibliometric Analysis

Causal inference in randomized trials will be the main topic of this short course on experimental design and analysis. The design of multilevel experiments, including cluster and multisite designs, statistical power, multiple comparisons, implementation fidelity, and methods for overcoming flaws in active experiments such as attrition and non-compliance, are among the topics covered in this course.

A randomized experiment's main objective is to provide reliable deductions regarding the causes of an intervention's effects. Randomization-based experiments have only lately emerged as the preferred approach for examining the impacts of social interventions, despite the fact that randomized experiments have been the preferred litmus test  for causal inference in medicine since the 1940s.

In the last two decades, for instance, there has been a significant change in the area of management research toward discovering the right interventions through randomized field trials. This course will cover the foundational elements of developing and carrying out experiments that satisfy the criteria of several R&D departments as well as those of foundation-originating funding programs focusing on intervention studies in the social sciences.

This program is delivered as a 4-day synchronous livestream virtual training via Zoom - a free video conferencing platform. Two lecture sessions with practical exercises will be held each day. Both sessions will be separated by a 60 mins break. Although you are strongly urged to attend in person, if you are unable to do so at the appointed time, you will be able to see the recorded lecture at a later time.

We are aware that it might be challenging to find time to engage in livestream classes. You can choose to take the entire course—or just a portion of it—asynchronously. You will still be able to access the course materials and conversations even if you are unable to participate in real-time by watching the video recordings, which will be made available within 24 hours of each session and will be available for three weeks following the seminar.

For all live and recorded sessions, there is closed captioning accessible. Spanish, Korean, and Italian are just a few of the languages that live captioning may be translated into. If you would like a short tutorial on how to get captions in your own language, please visit this page.

What the course covers

This course will demonstrate practical applications of contemporary techniques for the design and conduct of experiments in real world settings especially for strategy intervention, but equally applicable to other managerial, social and medical interventions.

Computing Requirements: You are highly advised to utilize your own laptop or desktop computer and install the instructor recommended software package(s) as this is hands-on training.

Who Should Register? Researchers, practitioners as well as corporate research and development  teams from all disciplines will find this course valuable. It will also be useful for anyone else who wants to learn how to organize, design, and analyze data from randomized experiments using software packages that are ready to deploy. No prior knowledge is required.

Brief Course Outline:

1. Theoretical foundations of causal inference in experiments
2. RT design options
3. Measurement of covariates and outcomes
4. Documenting treatment versus control conditions
5. Statistical models for impacts on continuous outcomes
6. Statistical models for impacts on categorical outcomes
7. Power analyses
8. Beyond basic impact analyses
9. Reporting in RTs
10. Demonstration / activity

Payment Details:

The $495 cost includes all required course materials.

All major payment cards are accepted.