Iekdensity is a Stata command, which is part of the ietoolkit package developed by DIME Analytics. Iekdensity allows users to easily plot the distribution of a variable based on treatment groups.
Multi-stage (cluster) sampling is a common sampling design in which the unit of randomization differs from the unit of observation. In other words, the unit at which the treatment is assigned (i.e.
A data map is a template designed by DIME Analytics for organizing the 3 main aspects of data work: data analysis, data cleaning, and data management.
The master do-file is the main do-file that calls upon and runs all the other do-files of a project. It plays a critical role throughout all stages of the research project and functions as a map to the data folder. This page outlines the components of a well-structured and replicable master do-file.
Optimal Design is free software designed by University of Michigan. It provides a useful platform on which researchers can visualize the relationship between different elements of the sample size formula when conducting power calculations during the research design stage. This page provides a general overview of and additional resources for Optimal Design.
ieduplicates is the second command in the Stata package created by DIME Analytics, iefieldkit.
iebaltab is a Stata command that produces balance tables, or difference-in-means tables, with multiple groups or treatment arms.
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- A typical impact evaluation team includes: Principal Investigator(s), Field Coordinator(s), and Research Assistant(s). There also is generally an IE coordinator who helps liaise between the research team and the field team.
Principal Investigators (PIs)
The Principal Investigator (PI) is the lead researcher for the impact evaluation, responsible for leading the evaluation design, data analysis, and the final academic paper.
In today's world of research, researchers regularly handle data, send it over the internet, and store it in the cloud. At any point, especially when the internet is involved, the data is exposed to some risk. Keeping data safe and encrypted is hence a key component of IRB requirements and research ethics.
Quasi-experimental methods are research designs that that aim to identify the impact of a particular intervention, program, or event (a "treatment") by comparing treated units (households, groups, villages, schools, firms, etc.) to control units.