Kaiser Reinhard, Woodruff Bradley A, Bilukha Oleg, Spiegel Paul B, Salama Peter
European Centre for Disease Prevention and Control, Stockholm, Sweden.
Disasters. 2006 Jun;30(2):199-211. doi: 10.1111/j.0361-3666.2006.00315.x.
A good estimate of the design effect is critical for calculating the most efficient sample size for cluster surveys. We reviewed the design effects for seven nutrition and health outcomes from nine population-based cluster surveys conducted in emergency settings. Most of the design effects for outcomes in children, and one-half of the design effects for crude mortality, were below two. A reassessment of mortality data from Kosovo and Badghis, Afghanistan revealed that, given the same number of clusters, changing sample size had a relatively small impact on the precision of the estimate of mortality. We concluded that, in most surveys, assuming a design effect of 1.5 for acute malnutrition in children and two or less for crude mortality would produce a more efficient sample size. In addition, enhancing the sample size in cluster surveys without increasing the number of clusters may not result in substantial improvements in precision.
对于计算整群调查的最有效样本量而言,对设计效应进行准确估计至关重要。我们回顾了在紧急情况下开展的9项基于人群的整群调查中7种营养与健康结局的设计效应。儿童结局的大多数设计效应以及粗死亡率设计效应的一半均低于2。对科索沃和阿富汗巴德吉斯的死亡率数据进行重新评估后发现,在聚类数量相同的情况下,改变样本量对死亡率估计精度的影响相对较小。我们得出结论,在大多数调查中,假设儿童急性营养不良的设计效应为1.5,粗死亡率的设计效应为2或更低,将得出更有效的样本量。此外,在不增加聚类数量的情况下增加整群调查的样本量可能不会显著提高精度。