J-PAL North America developed this pair of resources to support the use of nonpublic administrative data for randomized evaluations. The guide provides general tips on how to obtain and use these data. The catalog of key US data sets provides agency-specific information on how to request data.
This document provides an outline on how to approach collecting cost information, what costs to include and exclude, and how detailed cost data should be.
This step-by-step guide uses data and an annotated Stata do-file to illustrate how a simple randomization can be carried out using Stata.
IPA's data publication guideline covers the principles of organizing and documenting data and code – illustrated using examples from Stata – at all steps of the project lifecycle with the goal of making research reproducible.
The PPI is a leading household poverty measurement tool, used by more than 500 organizations around the world, to measure household poverty, improve targeting and social performance, and track changes in welfare. It is a country-specific ten-question scorecard that estimates whether a particular household is living below the poverty line.
Slides: Generalizability Framework
A Practical Guide to Measuring Women and Girls’ Empowerment in Impact Evaluations
This guide offers practical tips for how to measure women and girls’ empowerment in impact evaluations.
A Practical Guide to Measuring Women and Girls’ Empowerment in Impact Evaluations: Appendix 1
Appendix 1 of A Practical Guide to Measuring Women and Girls’ Empowerment in Impact Evaluations provides a catalogue of examples of survey questions and modules related to women and girls’ empowerment that have been used by J-PAL affiliated researchers in previous impact evaluations.
A Practical Guide to Measuring Women and Girls’ Empowerment in Impact Evaluations: Appendix 2
Appendix 2 of A Practical Guide to Measuring Women and Girls’ Empowerment in Impact Evaluations includes examples of non-survey instruments that can be used to measure women’s empowerment, pros and cons for each approach, and tips on how to use them.
Six Rules of Thumb for Determining Sample Size and Statistical Power
A guide for policymakers and practitioners that outlines the main factors that affect statistical power and sample size, and demonstrates how to design a high-powered randomized evaluation.
Poster: Real-World Challenges to Randomization and Their Solutions
A poster that summarizes the key takeaways and visuals from the guide: Real-World Challenges to Randomization and Their Solutions.
In this Stata module, you have some Stata experience (say in a college class) but would not consider yourself particularly comfortable with the program. You are very familiar with the following concepts:
- Descriptive commands such as summarize, tabulate, and list
- Conditions: if, and (&), and or (|)
- Data manipulation commands such as generate, replace, and drop
You are likely somewhat familiar with:
- Creating and writing do-files
- Sorting and saving datasets