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Network Psychometrics with R

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advanced psychometric network techniques
bnlearn
bootnet
Category=GPS
Category=JMB
Category=JMBT
causal inference
cluster detection
clustering coefficients
Conditional Independence
cross-sectional data
data science
Data Sets
degree distributions
Directed Acyclic Graphs
Edge Weight
Edges Included
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
estimation algorithm
Fixed Effects Analysis
Gaussian Graphical Models
Global Clustering Coefficient
graphical model estimation
graphicalVAR
GVAR
Ising Model
Lasso Estimation
Lasso Regularization
layout design
longitudinal data analysis
mixed data sets
mixed graphical models
mlVAR
Model Selection Algorithms
Multi-level Estimation
Multidimensional Item Response Theory Model
network psychometrics
network structures
Network Visualization Techniques
Partial Correlation Networks
PMRF
point estimates
Positive Manifold
practical exercises
pruning
psychological measurement
psychonetrics
qgraph
Qgraph Package
R
regularization
resilience
RStudio
Single Measurement Data
social network analysis
statistical inference methods
statistical models
Structural Var Model
sudden transitions
SVAR
Symptom Network
Synthetic Control Methods
temporal networks
Threshold Var Model
time series modelling
Time Vary Var Model
turtorial
Var Model
variance-covariance matrices
Vice Versa
violations of stationarity

Product details

  • ISBN 9780367628765
  • Weight: 640g
  • Dimensions: 174 x 246mm
  • Publication Date: 31 Mar 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Description

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.
About

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.