Resumé
Originalsprog | Engelsk |
---|---|
Tidsskrift | Policy Studies Journal |
Vol/bind | 40 |
Udgave nummer | 3 |
Sider (fra-til) | 375-401 |
ISSN | 0190-292X |
DOI | |
Status | Udgivet - aug. 2012 |
Citer dette
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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 tidsskrift › Tidsskriftartikel › Forskning › peer review
TY - JOUR
T1 - Statistical network analysis for analyzing policy networks
AU - Robins, Garry
AU - Lewis, Jenny
AU - Wang, Peng
PY - 2012/8
Y1 - 2012/8
N2 - 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.
AB - 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.
KW - social network models
KW - statistical models
KW - quadratic assignment procedure
KW - exponential random graph models
KW - stochastic actor-oriented models
KW - Innovation
U2 - 10.1111/j.1541-0072.2012.00458.x
DO - 10.1111/j.1541-0072.2012.00458.x
M3 - Journal article
VL - 40
SP - 375
EP - 401
JO - Policy Studies Journal
JF - Policy Studies Journal
SN - 0190-292X
IS - 3
ER -