Description
| Product ID: | 9781316610855 |
| Product Form: | Paperback / softback |
| Country of Manufacture: | US |
| Series: | Analytical Methods for Social Research |
| Title: | Inferential Network Analysis |
| Authors: | Author: Bruce A. Desmarais, Skyler J. Cranmer, Jason W. Morgan |
| Page Count: | 314 |
| Subjects: | Research methods: general, Research methods: general, Social research and statistics, Political structure and processes, Organizational theory and behaviour, Social research & statistics, Political structure & processes, Organizational theory & behaviour |
| Description: | Select Guide Rating Introduces foundational statistical models for network data, augmenting theoretical discussion with applications across the social sciences implemented in the R language. An introductory text or reference for researchers, graduate students, and advanced undergraduate students across the social, mathematical, computational and physical sciences. 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. |
| Imprint Name: | Cambridge University Press |
| Publisher Name: | Cambridge University Press |
| Country of Publication: | GB |
| Publishing Date: | 2020-11-19 |
