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Field
Primary Outcomes (End Points)
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Before
Milk production and sales
Health indicators such as incidence of vomiting, diarrhea, coughing and fever
Time use: times spent on fetching water, grazing/watering livestock, non-farming jobs, schooling and leisure
Water availability and allocation
Subjective and Mental Well-Being: Self-reported overall satisfaction with life, Index of mental well-being and access to water.
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After
Milk production and sales
Health indicators such as incidence of diarrhea
Time use
Water availability and allocation
Subjective well-being
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Field
Power calculation: Minimum Detectable Effect Size for Main Outcomes
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Before
Using administrative data on monthly milk sales with 12 pre-intervention and 18 post-intervention measurements with an expected across-measurement correlation of 0.75 (based on baseline administrative data), we expect to be able to detect an intent-to-treat effect of on milk sales of 6 percentage points at 80% power with 617 farmers in each arm. For our milk production and child health outcomes, we will conduct monthly SMS surveys. For production, we assume autocorrelation of X, and for child health we assume autocorrelation of X. With Y (less than 12, presumably) pre-intervention measures and Z post-intervention measures, we expect to be able to detect intent-to-treat effects of X and Y, respectively, at 80% power with X farmers in each arm. To account for margin of error, we aim to conduct the baseline survey with 1500 households and assign 750 farmers to the treatment group.
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After
Using administrative data on monthly milk sales with 12 pre-intervention and 18 post-intervention measurements with an expected across-measurement correlation of 0.75 (based on baseline administrative data), we expect to be able to detect an intent-to-treat effect on milk sales of 6 percentage points at 80% power with 617 farmers in each arm. To account for margin of error, we aim to conduct the baseline survey with 1500 households and assign 750 farmers to the treatment group.
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