Inferential Network Analysis

ISBN-13: 9781316610855 / Angielski / Miękka / 2021 / 314 str.

Jason W. (The Ohio State University) Morgan

Opis

Pioneering introduction of unprecedented breadth and scope to inferential and statistical methods for network analysis.

Recenzje

'The family of exponential random graph models have advanced with a number of extensions in recent years, many of them developed by the present authors. Encapsulating these advances with other methods of inferential analysis in a single reference that combines essential theory with hands-on examples makes this book a must-have for network modeling practitioners who want to use these powerful tools.' Peter Mucha, UNC Chapel Hill

Spis treści

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.

O autorze

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. 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.