The Estimation of Active Social Network Size of the Iranian Population

Azam Rastegari, Saiedeh Haji-Maghsoudi, Aliakbar Haghdoost, Mohsen Shatti, Termeh Tarjoman, Mohammad Reza Baneshi


Objectives: 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. Methods: 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. Results: 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. Conclusion: 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.

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Copyright (c) 2013 Azam Rastegari, Saiedeh Haji-Maghsoudi, Aliakbar Haghdoost, Mohsen Shatti, Termeh Tarjoman, Mohammad Reza Baneshi

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Global Journal of Health Science   ISSN 1916-9736(Print)   ISSN 1916-9744(Online)


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