Inferential Network Analysis

Erscheinungsjahr 2020
ISBN: 978-1-316-61085-5
Verlag: Cambridge University Press

Buch, Englisch, 250 Seiten, Format (B × H): 149 mm x 222 mm, Gewicht: 474 g

Reihe: Analytical Methods for Social Research

This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.

Autoren/Hrsg.

Desmarais, Bruce A.

Cranmer, Skyler J.

Morgan, Jason W.

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Organisationstheorie, Organisationssoziologie, Organisationspsychologie
• Sozialwissenschaften Politikwissenschaft Politische Systeme
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Forschungsmethodik, Wissenschaftliche Ausstattung

Inhaltsverzeichnis

Part I. Dependence and Interdependence: 1. Promises and Pitfalls of Inferential Network Analysis; 2. Detecting and Adjusting for Network Dependencies; Part II. The Family of Exponential Random Graph Models (ERGMs): 3. The Basic ERGM; 4. ERGM Specification; 5. Estimation and Degeneracy; 6. ERG Type Models for Longitudinally Observed Networks; 7. Valued-Edge ERGMs: The Generalized ERGM (GERGM); Part III. Latent Space Network Models: 8. The Basic Latent Space Model; 9. Identification, Estimation and Interpretation of the Latent Space Model; 10. Extending the Latent Space Model.

Über Autor(innen)

Morgan, Jason W.
Jason William Morgan is the Vice President for Behavioural Intelligence: Aware, and visiting scholar in Political Science at The Ohio State University.

Cranmer, Skyler J.
Skyler J. Cranmer is the Carter Phillips and Sue Henry Professor of Political Science at The Ohio State University.

Desmarais, Bruce A.
Bruce A. Desmarais is the DeGrandis-McCourtney Early Career Professor in Political Science at Penn State University.