Cameron A R, Baldock F C
Lao-Australian Animal Health Project, Vientiane, Laos.
Prev Vet Med. 1998 Feb 6;34(1):19-30. doi: 10.1016/s0167-5877(97)00073-1.
Disease in livestock populations tends to cluster at the herd level. In order to account for this--and to overcome the problems of simple random sampling from a very large population--large-scale livestock surveys usually involve two-stage sampling. However, the use of two-stage sampling presents particular problems for sample-size calculation and analysis. We developed a probability formula for two-stage sampling, initially based on the assumption of a perfect test. We used this formula to demonstrate how combinations of first-stage (number of herds) and second-stage (number of animals in selected herds) sample sizes can be altered to achieve a least-cost survey, and used simulation to validate the formula. To overcome the unrealistic assumption of a perfect test, we then applied an exact-probability formula (which takes imperfect tests and finite population sizes into account) to the two-stage sampling design. An example is given which shows how implementing the formula with the FreeCalc computer program allows least-cost first and second-stage sample sizes to be calculated.
家畜群体中的疾病往往在畜群层面聚集。为了考虑到这一点，并克服从非常大的群体中进行简单随机抽样的问题，大规模家畜调查通常涉及两阶段抽样。然而，两阶段抽样的使用给样本量计算和分析带来了特殊问题。我们最初基于完美检测的假设开发了一个两阶段抽样的概率公式。我们使用这个公式来展示如何改变第一阶段（畜群数量）和第二阶段（所选畜群中的动物数量）样本量的组合以实现成本最低的调查，并使用模拟来验证该公式。为了克服完美检测这一不现实的假设，我们随后将一个精确概率公式（该公式考虑了不完美检测和有限总体规模）应用于两阶段抽样设计。给出了一个示例，展示了如何使用FreeCalc计算机程序实施该公式来计算成本最低的第一阶段和第二阶段样本量。
