Rastegari Azam, Haji-Maghsoudi Saiedeh, Haghdoost Aliakbar, Shatti Mohsen, Tarjoman Termeh, Baneshi Mohammad Reza
Kerman University of Medical Sciences, Kerman, Iran.
Glob J Health Sci. 2013 Jun 17;5(4):217-27. doi: 10.5539/gjhs.v5n4p217.
The size of active network (C) of Iranian population is a very important parameter to estimate the size of unknown population using Network Scale Up (NSU) technique. However, there is little information about this parameter not only in Iran but also in other countries in Middle East region. Based on these needs, the aim of this paper is to estimate C for the Iranian population.
Based on available national statistics, 23 reference groups, with known population sizes were selected. Using multistage sampling method, 7454 individuals were recruited randomly around the country. We asked from our samples how many people they knew from each of the reference groups. Using NSU formulae, we maximized the goodness of fit of our estimation about the size of the reference groups by fitting the best C. However, the final C was set by excluding some of the reference groups with no added information; these inappropriate groups were selected by two techniques; regression, and ratio based approaches.
Applying regression and ratio based approaches the estimated C was 308 and 380 respectively. The Pearson correlation coefficient between the real and estimated size of reference groups (based on our C) in both methods was above 0.95. However, results of ratio based had better performance. We saw that the network of males, singles, younger age groups, and those with higher education was larger than those in other groups.
It seems that C in Iran is higher than that in developed countries, possibly because of its social structure. Because of cultural and social similarities in Middle East courtiers, C in other countries also might be higher than that in developed countries.
伊朗人口的活跃网络规模(C)是使用网络扩大法(NSU)估算未知人口规模的一个非常重要的参数。然而,不仅在伊朗,中东地区其他国家关于这个参数的信息也很少。基于这些需求,本文旨在估算伊朗人口的C值。
根据现有的国家统计数据,选择了23个已知人口规模的参考群体。采用多阶段抽样方法,在全国范围内随机招募了7454人。我们询问样本中他们认识每个参考群体中的多少人。使用NSU公式,通过拟合最佳的C值,使我们对参考群体规模的估计拟合优度最大化。然而,最终的C值是通过排除一些没有额外信息的参考群体来确定的;这些不合适的群体通过两种技术来选择:回归法和基于比率的方法。
应用回归法和基于比率的方法,估计的C值分别为308和380。两种方法中参考群体实际规模与估计规模(基于我们确定的C值)之间的皮尔逊相关系数均高于0.95。然而,基于比率的方法结果表现更好。我们发现男性、单身人士、较年轻年龄组以及受过高等教育者的网络规模大于其他群体。
伊朗的C值似乎高于发达国家,可能是由于其社会结构。由于中东国家在文化和社会方面的相似性,其他国家的C值也可能高于发达国家。