Allow for uncertainty: calculate best-case/worst-case sample size to select For example, for a study involving screening in which only 12-15% of the households will have an eligible person, and you want to end up with 200 completed cases, you might project the following situation, assuming occupancy rates of 94-96% and response rates of 45-50%: Best case OR = .96, ER = .15, RR = .50 Required sample size = 200 / (.96 * .15 * .50) = 2,778 Worst case OR = .94, ER = .12, RR = .45 Required sample size = 200 / (.94 * .12 * .45) = 3,940 In this situation, you should select a large enough sample for the worst-case scenario. Then subselect at random enough sample for the best-case scenario, and start the survey with those sample selections. But be prepared to add more selections as needed, up to the sample size required for your worst-case scenario. Source of information on these factors: Field outcome reports for previous studies HANDOUT C. Administer the Sample by Using Replicates or a Reserve Sample In the example above, begin field work with at least 2,778 sample units, but be prepared to put up to about 3,940 into the field. In this situation, you could think of designing a sample of 4,000 households, which you would then divide at random into 16 replicates of 250 each. You would begin fieldwork with 11 of the replicates, for an initial sample of 2,750. The other 5 replicates would be used as needed. (If necessary, a partial replicate could also be used, by dividing a full replicate into random parts.) The various adjustment factors be monitored as field work proceeds, to see if field results are getting closer to the best-case or to the worst-case scenario. As soon as it became clear that the best-case scenario was not going to materialize, you would start putting in some of the reserve sample. Remember that you must complete fieldwork on all of the replicates or reserves that you put into the field. If you just stop doing callbacks in a replicate when you reach a target number of completes, you will only get the easy cases in that replicate, and your
Allow for uncertainty: calculate best-case/worst-case sample size to select For example, for a study involving screening in which only 12-15% of the households will have an eligible person, and you want to end up with 200 completed cases, you might project the following situation, assuming occupancy rates of 94-96% and response rates of 45-50%: Best case OR = .96, ER = .15, RR = .50 Required sample size = 200 / (.96 * .15 * .50) = 2,778 Worst case OR = .94, ER = .12, RR = .45 Required sample size = 200 / (.94 * .12 * .45) = 3,940 In this situation, you should select a large enough sample for the worst-case scenario. Then subselect at random enough sample for the best-case scenario, and start the survey with those sample selections. But be prepared to add more selections as needed, up to the sample size required for your worst-case scenario. Source of information on these factors: Field outcome reports for previous studies HANDOUT C. Administer the Sample by Using Replicates or a Reserve Sample In the example above, begin field work with at least 2,778 sample units, but be prepared to put up to about 3,940 into the field. In this situation, you could think of designing a sample of 4,000 households, which you would then divide at random into 16 replicates of 250 each. You would begin fieldwork with 11 of the replicates, for an initial sample of 2,750. The other 5 replicates would be used as needed. (If necessary, a partial replicate could also be used, by dividing a full replicate into random parts.) The various adjustment factors be monitored as field work proceeds, to see if field results are getting closer to the best-case or to the worst-case scenario. As soon as it became clear that the best-case scenario was not going to materialize, you would start putting in some of the reserve sample. Remember that you must complete fieldwork on all of the replicates or reserves that you put into the field. If you just stop doing callbacks in a replicate when you reach a target number of completes, you will only get the easy cases in that replicate, and your
Sampling_outline.docx