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4.8
54 reviewsStatistics in the Social Sciences: Current Methodological Developments presents new and exciting statistical methodologies to help advance research and data analysis across the many disciplines in the social sciences. Quantitative methods in various subfields, from psychology to economics, are under demand for constant development and refinement. This volume features invited overview papers, as well as original research presented at the Sixth Annual Winemiller Conference: Methodological Developments of Statistics in the Social Sciences, an international meeting that focused on fostering collaboration among mathematical statisticians and social science researchers.
The book provides an accessible and insightful look at modern approaches to identifying and describing current, effective methodologies that ultimately add value to various fields of social science research. With contributions from leading international experts on the topic, the book features in-depth coverage of modern quantitative social sciences topics, including:
Correlation Structures
Structural Equation Models and Recent Extensions
Order-Constrained Proximity Matrix Representations
Multi-objective and Multi-dimensional Scaling
Differences in Bayesian and Non-Bayesian Inference
Bootstrap Test of Shape Invariance across Distributions
Statistical Software for the Social Sciences
Statistics in the Social Sciences: Current Methodological Developments is an excellent supplement for graduate courses on social science statistics in both statistics departments and quantitative social sciences programs. It is also a valuable reference for researchers and practitioners in the fields of psychology, sociology, economics, and market research.Content:
Chapter 1 Analysis of Correlation Structures: Current Status and Open Problems (pages 1–36): Peter M. Bentler and Victoria Savalei
Chapter 2 Overview of Structural Equation Models and Recent Extensions (pages 37–79): Kenneth A. Bollen, Daniel J. Bauer, Sharon L. Christ and Michael C. Edwards
Chapter 3 Order?Constrained Proximity Matrix Representations: Ultrametric Generalizations and Constructions with MATLAB (pages 81–112): Lawrence Hubert, Hans?Friedrich Kohn and Douglas Steinley
Chapter 4 Multiobjective Multidimensional (City?Block) Scaling (pages 113–133): Michael J. Brusco, Stephanie Stahl and J. Dennis Cradit
Chapter 5 Critical Differences in Bayesian and Non?Bayesian Inference and why the Former is Better (pages 135–157): Jeff Gill
Chapter 6 A Bootstrap Test of Shape Invariance Across Distributions (pages 159–174): Jeffrey N. Rouder, Paul L. Speckman, Douglas Steinley, Michael S. Pratte and Richard D. Morey
Chapter 7 Statistical Software for the Social Sciences (pages 175–189): Joseph M. Hilbe
Chapter 8 Conclusion: Roundtable Discussion (pages 191–194): Stanislav Kolenikov, Douglas Steinley and Lori Thombs
