Statistical network analysis for analyzing policy networks

Garry Robins, Jenny Lewis, Peng Wang

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

To analyze social network data using standard statistical approaches is to risk incorrect inference. The dependencies among observations implied in a network conceptualization undermine standard assumptions of the usual general linear models. One of the most quickly expanding areas of social and policy network methodology is the development of statistical modeling approaches that can accommodate such dependent data. In this article, we review three network statistical methods commonly used in the current literature: quadratic assignment procedures, exponential random graph models (ERGMs), and stochastic actor-oriented models. We focus most attention on ERGMs by providing an illustrative example of a model for a strategic information network within a local government. We draw inferences about the structural role played by individuals recognized as key innovators and conclude that such an approach has much to offer in analyzing the policy process.
OriginalsprogEngelsk
TidsskriftPolicy Studies Journal
Vol/bind40
Udgave nummer3
Sider (fra-til)375-401
ISSN0190-292X
DOI
StatusUdgivet - aug. 2012

Citer dette

Robins, Garry ; Lewis, Jenny ; Wang, Peng. / Statistical network analysis for analyzing policy networks. I: Policy Studies Journal. 2012 ; Bind 40, Nr. 3. s. 375-401.
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Statistical network analysis for analyzing policy networks. / Robins, Garry; Lewis, Jenny; Wang, Peng.

I: Policy Studies Journal, Bind 40, Nr. 3, 08.2012, s. 375-401.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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