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A systematic, innovative introduction to the field of network analysis, Network Psychometrics with R: A Guide for Behavioral and Social Scientists provides a comprehensive overview of and guide to both the theoretical foundations of network psychometrics as well as modelling techniques developed from this perspective.
Written by pioneers in the field, this textbook showcases cutting-edge methods in an easily accessible format, accompanied by problem sets and code. After working through this book, readers will be able to understand the theoretical foundations behind network modelling, infer network topology, and estimate network parameters from different sources of data. This book features an introduction on the statistical programming language R that guides readers on how to analyse network structures and their stability using R. While Network Psychometrics with R is written in the context of social and behavioral science, the methods introduced in this book are widely applicable to data sets from related fields of study. Additionally, while the text is written in a non-technical manner, technical content is highlighted in textboxes for the interested reader.
Network Psychometrics with R is ideal for instructors and students of undergraduate and graduate level courses and workshops in the field of network psychometrics as well as established researchers looking to master new methods.
This book is accompanied by a companion website with resources for both students and lecturers.
List of contents
I: Network Science in R 1 Network Perspectives 2 Short Introduction to R 3 Descriptive Analysis of Network Structures 4 Constructing and Drawing Networks in
qgraph 5 Association and Conditional Independence;
II: Estimating Undirected Network Models 6 Pairwise Markov Random Fields 7 Estimating Network Structures using Model Selection 8 Network Stability, Comparison, and Replicability;
III: Network Models for Longitudinal Data 9 Longitudinal Design Choices: Relating Data to Analysis 10 Network Estimation from Time Series and Panel Data 11 Modeling Change in Networks;
IV: Theory and Causality 12 Causal Inference 13 Idealized Modeling of Psychological Dynamics
About the author
Adela-Maria Isvoranu is postdoctoral researcher of psychology at the University of Amsterdam.
Sacha Epskamp is assistant professor of psychological methods at the University of Amsterdam.
Lourens J. Waldorp is associate professor of psychology at the University of Amsterdam.
Denny Borsboom is professor of psychology at the University of Amsterdam.
Summary
A systematic, innovative introduction to the field of network analysis, Network Psychometrics with R: A Guide for Behavioral and Social Scientists provides a comprehensive overview of and guide to both the theoretical foundations of network psychometrics as well as modelling techniques developed from this perspective.
