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Bayesian Methods
An Update of the Most Popular Graduate-Level Introductions to Bayesian Statistics for Social ScientistsNow that Bayesian modeling has become standard, MCMC is well understood and …
Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach
Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach is aimed at statisticians and quantitative social, economic and public health students and researchers who work …
Analyzing Spatial Models of Choice and Judgment
With recent advances in computing power and the widespread availability of preference, perception and choice data, such as public opinion surveys and legislative voting, the …
Handling Missing Data in Social Research
For social scientists, it is often confusing how to determine when missing data is a problem in analyses and how to handle it. This book presents a comprehensive overview of the …
Latent Markov Models for Longitudinal Data
Drawing on the authors’ extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data focuses on the formulation of latent Markov …
Handbook of Item Response Theory
Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume 3: Applications presents applications of item response theory to …
Applied Regularization Methods for the Social Sciences
Researchers in the social sciences are faced with complex data sets in which they have relatively small samples and many variables (high dimensional data). Unlike the various …
Big Data and Social Science
Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of …
Understanding Elections through Statistics
Elections are random events.From individuals deciding whether to vote, to individuals deciding who to vote for, to election authorities deciding what to count, the outcomes of …
A Generalized Framework for Item Response Models
This advanced textbook goes beyond the current limits of item response modeling to enhance understanding and help readers be more creative in the development and usage of the …
Analysis of Integrated Data
The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and …
Introduction to R for Social Scientists
Introduction to R for Social Scientists: A Tidy Programming Approach introduces the Tidy approach to programming in R for social science research to help quantitative researchers …