

Inferential Network Analysis by Skyler J Cranmer
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.-
Data Analysis Using Regression and Multilevel/Hierarchical Models
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Regression and Other Stories
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Counterfactuals and Causal Inference
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Essential Mathematics for Political and Social Research
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Multiverse Analysis
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Spatial Analysis for the Social Sciences
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Time Series Analysis for the Social Sciences
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Causal Mediation Analysis
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Statistical Modeling and Inference for Social Science
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Ecological Inference
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Event History Modeling
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Computational Social Science
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Formal Models of Domestic Politics
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Spatial Models of Parliamentary Voting
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Maximum Likelihood for Social Science
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Political Game Theory
| SKU | Unavailable |
| ISBN 13 | |
| ISBN 10 | |
| Title | Inferential Network Analysis |
| Author | Skyler J Cranmer |
| Series | |
| Condition | Unavailable |
| Binding Type | |
| Publisher | |
| Year published | |
| Number of pages | |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |
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