Difference between revisions of "Monitoring Data"
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Monitoring data is collected to understand the implementation of the '''assigned treatment''' in the field. Typically, [[Survey Pilot|survey]] round data helps us understand changes in the outcome '''variables''' throughout the duration of the project, and monitoring data helps us understand how these changes are related to the intervention of our '''treatment'''. For example, monitoring data could be data on who actually received the '''treatment''' and if it was implemented according to the research design. Our [[Data Analysis|analysis]] might be invalid if we do not have this information and base our '''analysis''' only on what was meant by the [[Impact Evaluation Team|research team]] to happen. Monitoring data helps us understand what is usually referred to as [https://en.wikipedia.org/wiki/Internal_validity internal validity]. | |||
== Read First == | |||
* '''Impact evaluations''' rely on many different [[Secondary Data Sources|sources of secondary data]] - administrative, [[Geo_Spatial_Data|geospatial]], [[Remote Sensing|sensors]], [[Telecom Data|telecom]], and [[Crowd-sourced Data|crowd-sourcing]]. | |||
* An important step in designing an '''impact evaluation''' is to evaluate which of the available data sources are best suited in a particular context. | |||
* Monitoring data is data that is collected to track the implementation of [[Randomized_Evaluations:_Principles_of_Study_Design#Step_2:_Randomization|treatment]] in a given '''impact evaluation'''. | |||
Latest revision as of 15:21, 20 May 2024
Monitoring data is collected to understand the implementation of the assigned treatment in the field. Typically, survey round data helps us understand changes in the outcome variables throughout the duration of the project, and monitoring data helps us understand how these changes are related to the intervention of our treatment. For example, monitoring data could be data on who actually received the treatment and if it was implemented according to the research design. Our analysis might be invalid if we do not have this information and base our analysis only on what was meant by the research team to happen. Monitoring data helps us understand what is usually referred to as internal validity.
Read First
- Impact evaluations rely on many different sources of secondary data - administrative, geospatial, sensors, telecom, and crowd-sourcing.
- An important step in designing an impact evaluation is to evaluate which of the available data sources are best suited in a particular context.
- Monitoring data is data that is collected to track the implementation of treatment in a given impact evaluation.