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Weight factor?

This question was posted the Assessment and Surveillance forum area and has 2 replies.

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Assaye

Normal user

21 Dec 2010, 10:47

Hi all, I have done a nutrition survey in 3 districts under a region and I want to know the average for the region. I think I have to calculate weight factor for each districts to get the regional level average. Would you please show me how to calculate weight factor? Thanks a lot!

Rossella

World food programme

Normal user

21 Dec 2010, 13:50

Hi, if you get from this link the WFP Comprehensive Food security and Vulnerability analisys guidelines, you can find in chapter 4 a detailed description on how to calculate weight factor. Hope it helps. http://www.wfp.org/food-security/guidelines

Mark Myatt

Epidemiologist at Brixton Health

Frequent user

21 Dec 2010, 14:49

The usual approach is to take a weighted average. To do this you need to have some idea of the (relative) population of each district. Example: Prevalences: District 1 : 7.6% District 2 : 9.3% District 3 : 5.4% If you have populations : District 1 : 123,000 District 2 : 91,000 District 3 : 52,000 Then the regional average is: (7.6 * 123000 + 9.3 * 91000 + 5.4 * 52000) / (123000 + 91000 + 52000) = 7.75% It is best to have population data but coarse weights based on relative sizes can work. Using the example above we might use small (1), medium (2), large (3) as coarse weights: p = (7.6 * 3 + 9.3 * 2 + 5.4 * 1) / (3 + 2 + 1) = 7.8% There are alternative approaches to weighting but they are usually, at bottom, just alternative ways of taking a weighted average. You may need to use these alternative methods with stats packages. The tricky bit is in calculating a confidence interval. This may be more difficult in your case as you already have a complex (i.e. cluster) sample at the district level. I suggest that you do this with software that can work with such a complex sample. A "rough and ready" approach would be to use a weighted average of the upper and lower 95% confidence limits from the district level samples. This is very much an approximate method. I hope this helps.

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