Mapping 5 Year Data

Derek L Thomas over 8 years ago

I’m wondering if there’s a best practice for reporting on/mapping the 5 year data with such wide margins of error, such as a 24.7% poverty rate w/ an MOE of +/-36.2, or even 0% poverty rate w/ an MOE of +/-28. For example, is there an MOE threshold that we could establish as too high to report on (leaving many counties in our map without data). This seems especially tricky when looking at differences between groups – such as difference between white and black poverty rates - when one race/ethnicity has a higher MOE than the other

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Dave Stinchcomb over 8 years ago

Sorry for the late entry in this discussion. I would add a caution about the Esri approach mentioned above which is based on the Coefficient of Variation (CV). CV's make sense when working with metrics like median income where it is important to normalize the estimate. However, CV's can be misleading when the estimate is near zero. For example if the estimate of the percent below poverty is 0% with an MOE of +/- 5%, the CV is infinitely large. The Esri approach would classify this as "Low Reliability" even though we can be quite confident that the percent below poverty is less than 5%.

In fact, I would not recommend using CVs with percentages at all. There is no need to normalize percentages - they are already normalized. I would just use the MOE directly to assess data reliability.
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Dave Stinchcomb over 8 years ago

Sorry for the late entry in this discussion. I would add a caution about the Esri approach mentioned above which is based on the Coefficient of Variation (CV). CV's make sense when working with metrics like median income where it is important to normalize the estimate. However, CV's can be misleading when the estimate is near zero. For example if the estimate of the percent below poverty is 0% with an MOE of +/- 5%, the CV is infinitely large. The Esri approach would classify this as "Low Reliability" even though we can be quite confident that the percent below poverty is less than 5%.

In fact, I would not recommend using CVs with percentages at all. There is no need to normalize percentages - they are already normalized. I would just use the MOE directly to assess data reliability.
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