Statistical analysis of network data—an application to diffusion of innovation

General methodology is developed here to deal with the association between a a binary variable and network connections with or without confounding covariates. Also the case when the network is observed at several time periods is treated. As an application we consider the diffusion of organic farming...

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Bibliographic Details
Main Authors: Jukka Nyblom A, Steve Borgatti B, Juha Roslakka C, Mikko A. Salo C
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.486.2099
http://www.analytictech.com/borgatti/papers/borgatti - statistical analysis of network data.pdf
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Summary:General methodology is developed here to deal with the association between a a binary variable and network connections with or without confounding covariates. Also the case when the network is observed at several time periods is treated. As an application we consider the diffusion of organic farming in the province of North Karelia in Finland. It turns out that organic farms are more clustered than would be expected under pure random allocation. The neighborhood effect remains when adjusting for the production lines of the farms. The spatio-temporal analysis shows that new adopters are more often found within the neighborhoods of each others and of earlier adopters.