A one-of-a-kind compilation of modern statistical methods designed to support and advance research across the social sciences
Statistics 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.
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STANISLAV KOLENIKOV, PhD, is Adjunct Assistant Professor of Statistics at the University of Missouri. He served as Program Chair of the Sixth Winemiller Conference. Dr. Kolenikov is an applied statistician with interests in structural equation modeling, survey statistics, econometrics, and statistical programming.
DOUGLAS STEINLEY, PhD, is Associate Professor of Psychology at the University of Missouri. Dr. Steinley currently conducts research in the areas of multivariate statistical methodology, cluster analysis, and social network analysis.
LORI THOMBS, PhD, is Associate Professor of Statistics and Director of the Social Science Statistics Center at the University of Missouri. Dr. Thombs has more than twenty years of academic experience, and she currently focuses her research on the areas of time series, resampling methods for correlated variables, and statistics education.
A one-of-a-kind compilation of modern statistical methods designed to support and advance research across the social sciences
Statistics 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.
A one-of-a-kind compilation of modern statistical methods designed to support and advance research across the social sciences
Statistics 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.
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