The analysis of social networks

被引:155
作者
O'Malley A.J. [1 ]
Marsden P.V. [2 ]
机构
[1] Department of Health Care Policy, Harvard Medical School, Boston, MA 02115-5899
[2] Department of Sociology, Harvard University, Cambridge, MA 02138
关键词
Correlation; Exponential random graph model; Latent-space model; Network autocorrelation model; Social network; Social relationship;
D O I
10.1007/s10742-008-0041-z
中图分类号
学科分类号
摘要
Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been proposed. More recently, interest in the analysis of social network data has grown among statisticians, who have developed more elaborate models and methods for fitting them to network data. This article reviews fundamentals of, and recent innovations in, social network analysis using a physician influence network as an example. After introducing forms of network data, basic network statistics, and common descriptive measures, it describes two distinct types of statistical models for network data: individual-outcome models in which networks enter the construction of explanatory variables, and relational models in which the network itself is a multivariate dependent variable. Complexities in estimating both types of models arise due to the complex correlation structures among outcome measures. © Springer Science+Business Media, LLC 2008.
引用
收藏
页码:222 / 269
页数:47
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