Difference between revisions of "Multi-stage (Cluster) Sampling"
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== Additional Resources == | == Additional Resources == | ||
* http://betterevaluation.org/en/evaluation-options/multistage | * http://betterevaluation.org/en/evaluation-options/multistage | ||
*DIME Analytics' presentations on randomization [https://github.com/worldbank/DIME-Resources/blob/master/stata1-5-randomization.pdf 1] and [https://github.com/worldbank/DIME-Resources/blob/master/stata2-5-randomization.pdf 2], the latter of which covers | *DIME Analytics' presentations on randomization [https://github.com/worldbank/DIME-Resources/blob/master/stata1-5-randomization.pdf 1] and [https://github.com/worldbank/DIME-Resources/blob/master/stata2-5-randomization.pdf 2], the latter of which covers multi-stage cluster sampling | ||
[[Category: Sampling & Power Calculations ]] | [[Category: Sampling & Power Calculations ]] | ||
Revision as of 19:45, 14 May 2019
Most impact evaluations rely on a multi-stage sampling design. This is when the unit of treatment assignment differs from the unit of survey respondent. For example, for an intervention assigned at the village level (treatment villages receive an intervention, control villages do not), the first stage of the sample would be village-level, and the second stage would be household-level (to select survey respondents).
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This article is part of the topic Sampling & Power Calculations
Additional Resources
- http://betterevaluation.org/en/evaluation-options/multistage
- DIME Analytics' presentations on randomization 1 and 2, the latter of which covers multi-stage cluster sampling