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# developing a methodology for a highly security compromised area. need guidence

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### Mark Myatt

Frequent user

26 Feb 2014, 16:21

Good to hear from you Najeeb (I believe we met last year in Pakistan). I will try to comment on all you sent. Sample size : A precision of 1.2% is very precise. At typical precision is 3% or even 5% (I think 1.2% is too precise for this sort of application). I will use a 95% CI of +/-3% on a 10% prevalence, a design effect of 2.0 (we do not know better ... you might), and a finite population correction in the example calculations below. The base formula is: ``` n = DEFF * [(p * (1 - p)) / (precision / 1.96)^2] n = 2.0 * ((0.1 * (1 - 0.1)) / (0.03 / 1.96)^2) n = 768 ``` We can apply a finite population correction (FPC) to this: ``` new.n = (old.n * population) / (old.n + (population - 1)) new.n = (768 * 2400) / (768 + (2400 - 1)) new.n = 582 ``` When you analyse the data you can apply another FPC as described in this post. If you plan to take many small samples then you might use DEFF = 1.5 in your sample size calculation. In these sorts of missions I prefer to take the smallest sample size (in terms of both the number of PSUs and the within-PSU sample size) that can meet my needs as it exposes me and my staff to less risk. WRT your (1) ... The setting makes PPS sample very difficult as you have no good prior information on populations. This is typical of emergency settings with displacement. I think your idea of a CSAS or other spatial stratification is a good one. Since this is not a PPS sample you will need to weight after data-collection. This means that you need to have some way of estimating the eligible population in each primary sampling unit (PSU). Posterior weighting is described in this post. WRT your (2) ...[/url] This looks like it might work. I would segment the community and take a part of the overall PSU sample from each segment. I think it is important to pilot the sampling method. A rule-of-thumb is that the sample should come from all over the PSU. If you do this then you will help to keep the DEFF low. In insecure areas it is a good idea to select a number of contingency clusters / locations that can be "swapped in" should a particular community be inaccessible. With a spatial sample you can chose the nearest (in terms of distance) sampling opportunity. Please pay close attention to your personal safety and that of your survey staff. Feel free to ask follow-up questions. I think you will need to think hard about how you will get the weights. We can review that here. I am in the field myself and may take a day to answer. I hope this helps.

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