Understanding Correlation Matrices

图书简介

Correlation matrices (along with their unstandardized counterparts, covariance matrices) underlie the majority the statistical methods that researchers use today. A correlation matrix is more than a matrix filled with correlation coefficients. The value of one correlation in the matrix puts constraints on the values of the others, and the multivariate implications of this statement is a major theme of the volume. Alexandria Hadd and Joseph Lee Rodgers cover many features of correlations matrices including statistical hypothesis tests, their role in factor analysis and structural equation modeling, and graphical approaches. They illustrate the discussion with a wide range of lively examples.

Series Editors Introduction \\ Preface \\ Acknowledgments \\ About the Authors \\ Chapter 1: Introduction \\ The Correlation Coefficient: A Conceptual Introduction \\ The Covariance \\ The Correlation Coefficient and Linear Algebra: Brief Histories \\ Examples of Correlation Matrices \\ Summary \\ Chapter 2: The Mathematics of Correlation Matrices \\ Requirements of Correlation Matrices \\ Eigenvalues of a Correlation Matrix \\ Pseudo-Correlation Matrices and Positive Definite Matrices \\ Smoothing Techniques \\ Restriction of Correlation Ranges in the Matrix \\ The Inverse of a Correlation Matrix \\ The Determinant of a Correlation Matrix \\ Examples \\ Summary \\ Chapter 3: Statistical Hypothesis Testing on Correlation Matrices \\ Hypotheses About Correlations in a Single Correlation Matrix \\ Hypotheses About Two or More Correlation Matrices \\ Testing for Linear Trend of Eigenvalues \\ Summary \\ Chapter 4: Methods for Correlation/Covariance Matrices as the Input Data \\ Factor Analysis \\ Structural Equation Modeling \\ Meta-Analysis of Correlation Matrices \\ Summary \\ Chapter 5: Graphing Correlation Matrices \\ Graphing Correlations \\ Graphing Correlation Matrices \\ Summary \\ Chapter 6: The Geometry of Correlation Matrices \\ What Is Correlation Space? \\ The 3 × 3 Correlation Space \\ Properties of Correlation Space: The Shape and Size \\ Uses of Correlation Space \\ Example Using 3 × 3 and 4 × 4 Correlation Space \\ Summary \\ Chapter 7: Conclusion \\ References \\ Index

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Understanding Correlation Matrices（Quantitative Applications in the Social Sciences） 了解相关矩阵 社会学史

Understanding Correlation Matrices（Quantitative Applications in the Social Sciences）

了解相关矩阵
社会学史