Cantitate/Preț
Produs
Total produse
Vezi coșul
Exploratory Factor Analysis de Holmes Finch

Exploratory Factor Analysis: Quantitative Applications in the Social Sciences, cartea 182

Autor Holmes Finch
en Limba Engleză Paperback – 2 dec 2019
A firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. This volume provides a solid foundation in exploratory factor analysis (EFA), which along with confirmatory factor analysis, represents one of the two major strands in this field. The book lays out the mathematical foundations of EFA; explores the range of methods for extracting the initial factor structure; explains factor rotation; and outlines the methods for determining the number of factors to retain in EFA. The concluding chapter addresses a number of other key issues in EFA, such as determining the appropriate sample size for a given research problem, and the handling of missing data.  It also offers brief introductions to exploratory structural equation modeling, and multilevel models for EFA. Example computer code, and the annotated output for all of the examples included in the text are available on an accompanying website.

Citește tot Restrânge

Din seria Quantitative Applications in the Social Sciences

  • Interpreting and Comparing Effects in Logistic, Probit, and Logit Regression
    Preț: 30605 lei
  • Data Analysis: An Introduction
    Preț: 26520 lei
  • Causal Analysis with Panel Data
    Preț: 27024 lei
  • Missing Data
    Preț: 26632 lei
  • Confidence Intervals
    Preț: 27028 lei
  • Multilevel Modeling
    Preț: 28754 lei
  • Agent-Based Models
    Preț: 29684 lei
  • Social Network Analysis
    Preț: 28863 lei
  • A Mathematical Primer for Social Statistics
    Preț: 28917 lei
  • Reliability and Validity Assessment
    Preț: 26574 lei
  • An Introduction to Exponential Random Graph Modeling
    Preț: 26765 lei
  • Factorial Survey Experiments
    Preț: 26949 lei
  • Multilevel Structural Equation Modeling
    Preț: 28808 lei
  • Gathering Social Network Data
    Preț: 28835 lei
  • Generalized Linear Models for Bounded and Limited Quantitative Variables
    Preț: 28782 lei
  • Multidimensional Item Response Theory
    Preț: 28754 lei
  • Argument-Based Validation in Testing and Assessment
    Preț: 28832 lei
  • Using Time Series to Analyze Long-Range Fractal Patterns
    Preț: 28754 lei
  • Rasch Models for Solving Measurement Problems: Invariant Measurement in the Social Sciences
    Preț: 28808 lei
  • Analyzing Textual Information: From Words to Meanings through Numbers
    Preț: 28863 lei
  • Confirmatory Factor Analysis
    Preț: 28782 lei
  • Sequence Analysis
    Preț: 28917 lei
  • Applied Bayesian Statistics
    Preț: 28937 lei
  • Longitudinal Network Models
    Preț: 28844 lei
  • Exploring Rating Scale Functioning for Survey Research
    Preț: 28944 lei
  • Introduction to Survey Sampling
    Preț: 28863 lei
  • Models for Innovation Diffusion
    Preț: 26990 lei
  • Analysis of Variance
    Preț: 28100 lei
  • Ecological Inference
    Preț: 27968 lei
  • Multivariate Tests for Time Series Models
    Preț: 28137 lei
  • Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models
    Preț: 28079 lei
  • Typologies and Taxonomies: An Introduction to Classification Techniques
    Preț: 28194 lei
  • Multiple Attribute Decision Making: An Introduction
    Preț: 28025 lei
  • Applied Logistic Regression Analysis
    Preț: 28248 lei
  • Chaos and Catastrophe Theories
    Preț: 27988 lei
  • Basic Math for Social Scientists: Concepts
    Preț: 27988 lei
  • Multidimensional Scaling
    Preț: 28100 lei
  • Calculus
    Preț: 28063 lei
  • Regression Models: Censored, Sample Selected, or Truncated Data
    Preț: 28025 lei
  • Tree Models of Similarity and Association
    Preț: 27968 lei
  • Computational Modeling
    Preț: 28157 lei
  • LISREL Approaches to Interaction Effects in Multiple Regression
    Preț: 28174 lei
  • Analyzing Repeated Surveys
    Preț: 28005 lei
  • Monte Carlo Simulation
    Preț: 28025 lei
  • Statistical Graphics for Univariate and Bivariate Data
    Preț: 28174 lei
  • Interaction Effects in Factorial Analysis of Variance
    Preț: 28174 lei
  • Odds Ratios in the Analysis of Contingency Tables
    Preț: 28042 lei

Preț: 28808 lei

Nou

Puncte Express: 432
Preț estimativ în valută:
5513€ • 5798$ • 4592£

Carte disponibilă

Livrare economică 14-28 decembrie
Livrare express 30 noiembrie-06 decembrie pentru 2319 lei

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781544339887
ISBN-10: 1544339887
Pagini: 144
Dimensiuni: 140 x 216 x 11 mm
Greutate: 0.18 kg
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Seria Quantitative Applications in the Social Sciences

Locul publicării:Thousand Oaks, United States

Recenzii

This text is a perfect resource for individuals seeking guidance on applied factor analysis, covering the fundamentals as well as introductions to more advanced aspects of factor analytic techniques. 

Finch provides a well-written and well-organized introduction to the conceptual and quantitative topics of exploratory and confirmatory factor analysis within a single, concise text. 

This is a thorough and readable introduction to exploratory factor analysis

Cuprins

Chapter One: Introduction to Factor Analysis
Latent and Observed Variables
The Importance of Theory in Doing Factor Analysis
Comparison of Exploratory and Confirmatory Factor Analysis
EFA and Other Multivariate Data Reduction Techniques
A Brief Word About Software
Outline of the Book
Chapter Two: Mathematical Underpinnings of Factor Analysis
Correlation and Covariance Matrices
The Common Factor Model
Correspondence Between the Factor Model and the Covariance Matrix
Eigenvalues
Error Variance and Communalities
Summary
Chapter Three: Methods of Factor Extraction in Exploratory Factor Analysis
Eigenvalues, Factor Loadings, and the Observed Correlation Matrix
Maximum Likelihood
Principal Axis Factoring
Principal Components Analysis
Principal Components Versus Factor Analysis
Other Factor Extraction Methods
Example
Summary
Chapter Four: Methods of Factor Rotation
Simple Structure
Orthogonal Versus Oblique Rotation Methods
Common Orthogonal Rotations
Common Oblique Rotations
Target Factor Rotation
Bifactor Rotation
Example
Deciding Which Rotation to Use
Summary
Appendix
Chapter Five: Methods for Determining the Number of Factors to Retain in Exploratory Factor Analysis
Scree Plot and Eigenvalue Greater Than 1 Rule
Objective Methods Based on the Scree Plot
Eigenvalues and the Proportion of Variance Explained
Residual Correlation Matrix
Chi-Square Goodness of Fit Test for Maximum Likelihood
Parallel Analysis
Minimum Average Partial
Very Simple Structure
Example
Summary
Chapter Six: Final Issues in Factor Analysis
Proper Reporting Practices for Factor Analysis
Factor Scores
Power Analysis and A Priori Sample Size Determination
Dealing With Missing Data
Exploratory Structural Equation Modeling
Multilevel EFA
Summary

Notă biografică

W. Holmes Finch (Ph.D. South Carolina) is the George and Frances Ball Distinguished Professor of Educational Psychology in the Department of Educational Psychology at Ball State University. Prior to coming to Ball State, he worked as a consultant in the Statistics Department at the University of South Carolina for 12 years advising faculty and graduate students on the appropriate statistical methods for their research. Dr. Finch teaches courses in statistical and research methodology as well as psychometrics and educational measurement. His research interests involve issues in psychometrics, including dimensionality assessment, differential item functioning, generalizability theory and unfolding models. In addition, he pursues research in multivariate statistics, particularly those involving nonparametric techniques. He is the co-author of Multilevel Modeling Using R (with Holden, J.E., & Kelley, K., CRC Press, 2014); Applied Psychometrics Using SAS (with French, B.F. & Immekus, J., Information Age, 2014); and Latent Variable Models in R (with French, B.F., Routledge, 2015).


Descriere

A firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. This volume provides a solid foundation in exploratory factor analysis (EFA), which along with confirmatory factor analysis, represents one of the two major strands in this field. The book lays out the mathematical foundations of EFA; explores the range of methods for extracting the initial factor structure; explains factor rotation; and outlines the methods for determining the number of factors to retain in EFA. The concluding chapter addresses a number of other key issues in EFA, such as determining the appropriate sample size for a given research problem, and the handling of missing data.  It also offers brief introductions to exploratory structural equation modeling, and multilevel models for EFA. Example computer code, and the annotated output for all of the examples included in the text are available on an accompanying website.