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Sample size estimation for follow up CSAS survey

This question was posted the Assessment and Surveillance forum area and has 1 replies.

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Anonymous 680

Quality Assuarance Officer

Normal user

5 Sep 2013, 07:47

We are doing a sort of follow up coverage assessment after two years of CMAM program. The project had a baseline coverage estimate in 2011 (used CSAS). The project targets >70% coverage by now. So, how shall we approach the task? 1. Use the one point 50%+/-10% 2. Use the classical difference of two proportions estimation and correct for size 3. any other way which I am not clear Thanks for your support

Mark Myatt

Frequent user

5 Sep 2013, 09:54

There are a few ways to do this. (A) A full SQUEAC. This will give you a lot of information on barriers to coverage as well as a coverage estimate. (B) A plain CSAS. You'd probably want to aim for a sample size suitable to estimating a proportion of 70% with a useful precision (i.e. +/- 10 or better). For this you'd need a sample size of 80 or more. (C) A Bayesian CSAS. This is as above but you can factor in what you already know about coverage from your previous CSAS, routine monitoring data, &c. to give a prior. You would combine this prior with new CSAS data using a beta-binomial conjugate analysis. The advantage of this approach is that you would need a smaller sample size as the prior contributes information. If (e.g.) you had a reasonable believe that coverage was most likely to be about 70% and very unlikely to be below 50% and extremely unlikely to be above 90% then a sample size of n = 42 might suffice to give you 10% precision whilst retaining some protection against bias from a misspecified prior. Details of this approach can be found in the SQUEAC / SLEAC technical reference and software is available here. (D) Use SLEAC. This is a cut-down CSAS type survey that provides a classification. A typical sample size is n = 40. Details of this approach can be found in the SQUEAC / SLEAC technical reference. I hope this is of some use.

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