Statistics in the Social Sciences : Current Methodological Developments

by Stanislav Kolenikov (Univ. of Missouri ); Lori Thombs (Univ. of Missouri ); Douglas Steinley (Univ. of Missouri )

• ISBN13: 9780470583326
• ISBN10: 0470583320
• Format: eBook
• Copyright: 2010-02-01
• Publisher: Wiley

Summary

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.

Table of Contents

List of Figures

List of Tables

Preface

Analysis of Correlation Structures: Current Status and Open Problems

Introduction

Correlation versus Covariance Structures

Estimation and Model Testing

Basic Asymptotic Theory

Distribution of T Under Model Misspecification

Distribution of T Under Weight Matrix Misspecification

Estimation and Testing with Arbitrary Distributions

Tests of Model Fit Under Distributional Misspecification

Scaled and Adjusted Statistics

Normal Theory Estimation and Testing

Elliptical Theory Estimation and Testing

Heterogeneous Kurtosis Theory Estimation and Testing

Least Squares Estimation and Testing

Example

Simulations

Data

Correlation Structure with ADF Estimation and Testing

Correlation Structure with Robust Least Squares Methods

Discussion

References

Overview of Structural Equation Models and Recent Extensions

Model Specification and Assumptions

Illustration of Special Cases

Modeling Steps

Multilevel SEM

The Between-and-Within Specification

Random Effects as Factors Specification

Summary and Comparison

Structural Equation Mixture Models

The Model

Estimation

Sensitivity to Assumptions

Direct and Indirect Applications

Summary

Item Response Models

Categorical CFA

CCFA Estimation

Item Response Theory

CCFA and IRT

Advantages and Disadvantages

Complex Samples and Sampling Weights

Complex Samples and Their Features

Probability (Sampling) Weights

Violations of SEM Assumptions

SEM Analysis Using Complex Samples with Unequal Probabilities of Selection

Future Research

Conclusion

References

Order-Constrained Proximity Matrix Representations

Introduction

Proximity Matrix for Illustration: Agreement Among Supreme Court Justices

Order-Constrained Ultrametrics

The M-file ultrafndxonfit.m

The M-file ultrafnd.confnd.rn

Representing an (Order-Constrained) Ultrametric

Alternative (and Generalizable) Graphical Representation for an Ultrametric

Alternative View of Ultrametric Matrix Decomposition

Ultrametric Extensions by Fitting Partitions Containing Contiguous Subsets

Ordered Partition Generalizations

Extensions to Additive Trees: Incorporating Centroid Metrics

References

Multiobjective Multidimensional (City-Block) Scaling

Introduction

City-Block MDS

Multiobjective City-Block MDS

The Metric Multiobjective City-Block MDS Model

The Nonmetric Multiobjective City-Block MDS Model

Combinatorial Heuristic

Numerical Examples

Example 1

Example 2

Summary and Conclusions

References

Critical Differences in Bayesian and Non-Bayesian Inference

Introduction

The Mechanics of Bayesian Inference

Example with Count Data

Comments on Prior Distributions

Specific Differences Between Bayesians and non-Bayesians

Paradigms For Testing

Change-point Analysis of Thermonuclear Testing Data

Conclusion

References

Bootstrap Test of Shape Invariance Across Distributions

Lack of Robustness of a Parametric Test

Development of a Nonparametric Shape Test

Example

Extension of the Shape Test

Characteristics of the Bootstrap Shape Test

Application

Conclusion

References

Statistical Software for the Social Sciences

Social Science Research: Primary Capabilities

Statistical Social Science Statistical Applications

R

SAS

SPSS

Stata

STATISTIC A

StatXact/LogXact

Statistical Application Utilities

Stat/Transfer

ePrint Professional

nQuery Advisor

Summary Comments

References

Conclusion: Roundtable Discussion

Index

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