It is possible to assess the difference between prevalence estimates returned by two surveys. A simple approach is to estimate the standard error in each survey:

then poole the two SEs:

and calculate a z-test:

The p-value is taken from the normal distribution (if abs(z) > 1.96 the p < 0.05).

You use an estimation approach:

I think you may have an issue with the sample size in the second "survey". The SE for the second "survey" will be wide. This means that you will not see a significant difference unless the difference is very large.

I hope this is of some use.

Just remembered ...

You will be able to get a bit more power if you use the mean MUAC (or mean WHZ, WAZ, HAZ) and test for differences between means rather than prevalences.

I still think you will have sample size issues.

Dear Mark,

Thank you so much for the guidance. I will use both methods see which one yield for any statistical difference, of course the last round sample is too small if any.

On another note, I saw in one of your conversation the value of and how to form a combined nutritional index for further analysis(WFH, WFA and HFA) but I seem to be at loss trying to locate it and get the information.

I will appreciate it if you can direct me to the link in your best convenient time.

Warmest regards.

Happy to help.

I think you mean the Composite Index of Anthropometric Failure (CIAF).

You can find the original article here.

Also, see here.

Thanks to Chris Hillbruner (Decision Support Advisor - FEWS NET) who writes ...

This is another interesting example of using CIAF, in this case to explore the relationship between mortality risk and the presence of multiple anthropometric deficits.

Hi all,

I am currently recruiting for a Nutrition Program Manager based in Liberia.

Please email me at dchandegra@international Medicalcorps.org.uk if you are interested.

Many thanks,

Dina