J-PAL promotes the publication of de-identified data from randomized evaluations ¹. This resource provides guidance on doing so in the form of a checklist for preparing data for submission. It also includes sample informed consent language and other considerations during project planning and...

Randomized evaluations require collaboration and communication between many stakeholders, including academic researchers, research staff, implementing partners, holders of administrative data, policymakers, and the community. These stakeholders have diverse viewpoints and specialized vocabularies...

This page compiles links to resources on software, user-written commands for randomized evaluations, coding in teams, and writing reproducible code. User-written commands listed below include common checks for randomized evaluations and faster versions of frequently used commands in Stata and R.

This resource is intended for researchers who are interested in collecting cost data and conducting comparative cost-effectiveness analysis (CEA) for their evaluation. It provides an overview of CEA, outlines the basic calculations and key assumptions, and provides two comparative CEA examples from...

Randomization for causal inference has a storied history. Controlled randomized experiments were invented by Charles Sanders Peirce and Joseph Jastrow in 1884. Jerzy Neyman introduced stratified sampling in 1934. Ronald A. Fisher expanded on and popularized the idea of randomized experiments and...