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Choices with Consequences #1: Outlier Treatment in Continuous Indicators
Key Takeaways The outlier problem in survey datasets Outliers in survey datasets can represent valid observations when they reflect trulyatypical cases within the sample or population. However, many outliers arise fromerrors. Three main types of errors can generate outliers: If left unaddressed, outliers can meaningfully distort summary statistics, variabledistributions, and analytical results. In practice, treating…
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Announcing A New Series: Indicator Choices With Consequences
What A series of blogs and technical briefs on the implications of alternative cleaning and variable construction decisions when constructing agricultural indicators. In this series, we will cover topics such as winsorization choices, representing women farmers and challenges constructing gender productivity gaps, inconsistencies interpreting the oft used phrase “improved seed,” and how the choice of…
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CRIFS Technical Brief: Understanding how Risk Affects Small-Scale Producer’s Decision-making
CRIFS TECHNICAL BRIEF 396c Risks in Food Systems: Understanding how Risk Affects Small-Scale Producer’s Decision-making Sat, 05/23/2026 AUTHORS: Joaquin Mayorga, C. Leigh Anderson, Didier Y. Alia Key messages RESEARCH TOPIC CATEGORY: Sustainable Agriculture & Rural Livelihoods GEOGRAPHIC FOCUS: Sub-Saharan Africa; South Asia Downloadable Documents Research Brief