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Latent Variables and Factor Analysis [Multiple-component retail product]

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  • Formaat: Multiple-component retail product, 1472 pages, kõrgus x laius: 234x156 mm, kaal: 5770 g, 4 Items, Contains 4 hardbacks
  • Sari: Sage Benchmarks in Social Research Methods
  • Ilmumisaeg: 19-Feb-2015
  • Kirjastus: Sage Publications Ltd
  • ISBN-10: 1446294609
  • ISBN-13: 9781446294604
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Latent Variables and Factor AnalysisSuurem pilt
  • Formaat: Multiple-component retail product, 1472 pages, kõrgus x laius: 234x156 mm, kaal: 5770 g, 4 Items, Contains 4 hardbacks
  • Sari: Sage Benchmarks in Social Research Methods
  • Ilmumisaeg: 19-Feb-2015
  • Kirjastus: Sage Publications Ltd
  • ISBN-10: 1446294609
  • ISBN-13: 9781446294604
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781446294604.html
Märksõnad:

This four-volume Major Work contains texts which explore both the foundations of latent variables and factor analysis, and specific contemporary challenges in the field.



This four-volume Major Work contains texts which explore both the foundations of latent variables and factor analysis, and specific contemporary challenges in the field.

The collection has been designed as a multi-disciplinary resource, with literature drawn from many different areas of study, such as sociology, psychology, education and political science.

In the editor’s introductory essay, a general approach to the meaning and use of latent variables in the social sciences is laid out, the basics of factor analysis and how it works are explained, and the logic that guided the selection of literature included in the collection is elaborated upon. The combination of these elements makes for a truly comprehensive and user-friendly research tool, invaluable to social scientists across a range of disciplines.

Volume One: The Conceptualization and Operationalization of Variables

Volume Two: Applications of Unmeasured Variables

Volume Three: Factor Analysis for Latent Variables

Volume Four: Advanced Topics

Arvustused

"Dr. Babones has brought together an important collection of articles on latent variables and factor analysis that applied researcher and practitioners will find essential for understanding methodological foundations, as well as relevant applications. This is necessary in a time when the amount of information on factor analysis can be overwhelming for both beginners and experts alike." -- Tom A Schmitt, PhD. "This collection is a wonderful resource for students who are planning to learn about this important method. The carefully-chosen papers and the editors introductory essays will greatly facilitate self-study in this field. Beginners will save substantial time to get the right direction in learning, especially when courses and workshops on factor analyses are not available. Meanwhile, the collection is also a valuable reader for instructors to teach these methods. I appreciate Professor Babones work in this collection, and I am sure many students and scholars will benefit from this publication."  -- Qiushi Feng These volumes provide a fine historical and comprehensive coverage of exploratory and confirmatory factor analysis. The theory and practical use of factor analysis are both superbly presented. At the same time, special attention is given to foundation issues in measurement, and how factor analysis relates to these issues. Researchers, students, and faculty members will find these volumes essential aids in deepening and broadening their knowledge and skills. -- Richard P. Bagozzi This is a carefully-selected and well-balanced set of key articles covering a wide range of issues in factor analysis and latent variable modeling. What is particularly impressive is the inclusion of "classic" papers from several disciplines that have shaped or even revolutionalized thinking on measurement and modeling. Both novice and experienced researchers across disciplines will strongly benefit from consulting this comprehensive reference work. Congratulations for putting together such an an excellent resource. -- Professor Adamantios Diamantopoulos

Appendix of Sources xi
Volume I The Conceptualization and Operationalization of Variables
1 Latent Variables and Factor Analysis
1(26)
Salvatore Babones
1 Perspectives on Measurement
2 The Presidential Address: Measurement and Conceptualization Problems -- The Major Obstacle to Integrating Theory and Research
27(20)
H.M. Blalock, Jr.
3 Detection and Determinants of Bias in Subjective Measures
47(18)
Kenneth A. Bollen
Pamela Paxton
4 Conventional Wisdom on Measurement: A Structural Equation Perspective
65(20)
Kenneth Bollen
Richard Lennox
5 Measurement in Sociology
85(8)
Floyd N. House
6 A History of Social Science Measurement
93(28)
Benjamin D. Wright
2 Construct Validity
7 Classical and Modern Methods of Psychological Scale Construction
121(20)
Leonard J. Simms
8 Construct Validity in Psychological Tests
141(26)
Lee J. Cronbach
Paul E. Meehl
9 Convergent and Discriminant Validation by the Multitrait-Multimethod Matrix
167(26)
Donald T. Campbell
Donald W. Fiske
10 Assessing Construct Validity in Organizational Research
193(42)
Richard P. Bagozzi
Youjae Yi
Lynn W. Phillips
11 The Empirical Assessment of Construct Validity
235(26)
Scott W. O'Leary-Kelly
Robert J. Vokurka
12 The Dangers of Poor Construct Conceptualization
261(10)
Scott B. MacKenzie
3 Item Response Theory
13 The New Rules of Measurement
271(16)
Susan E. Embretson
14 Applying Item Response Theory (IRT) Modeling to Questionnaire Development, Evaluation, and Refinement
287(22)
Maria Orlando Edelen
Bryce B. Reeve
15 The Past and Future of Multidimensional Item Response Theory
309
Mark D. Reckase
Volume II Exploratory and Confirmatory Factor Analysis
4 Exploratory Factor Analysis
16 Exploratory Factor Analysis: A Users' Guide
3(18)
Eamonn Ferguson
Tom Cox
17 Evaluating the Use of Exploratory Factor Analysis Psych9logical Research
21(42)
Leandre R. Fabrigar
Duane T. Wegener
Robert C. MacCallum
Erin J. Strahan
18 The Quality of Factor Solutions in Exploratory Factor Analysis: The Influence of Sample Size, Communality, and Overdetermination
63(22)
Kristine Y. Hogarty
Constance V. Hines
Jeffrey D. Kromrey
John M. Ferron
Karen R. Mumford
19 A Review and Evaluation of Exploratory Factor Analysis Practices in Organizational Research
85(24)
James M. Conway
Allen I. Huffcutt
20 Use of Exploratory Factor Analysis in Published Research: Common Errors and Some Comment on Improved Practice
109(24)
Robin K. Henson
J. Kyle Roberts
21 Evaluating the Use of Exploratory Factor Analysis in Developmental Disability Psychological Research
133(24)
Megan Norris
Luc Lecavalier
5 Confirmatory Factor Analysis
22 Factor Analytic Models: Viewing the Structure of an Assessment Instrument from Three Perspectives
157(26)
Barbara M. Byrne
23 The Generality of Criminal Behavior: A Confirmatory Factor Analysis of the Criminal Activity of Sex Offenders in Adulthood
183(22)
Patrick Lussier
Marc LeBlanc
Jean Proulx
24 Confirmatory Factor Analyses of Multitrait-Multimethod Data: Many Problems and a Few Solutions
205(34)
Herbert W. Marsh
25 Sample Size and Number of Parameter Estimates in Maximum Likelihood Confirmatory Factor Analysis: A Monte Carlo Investigation
239(18)
Dennis L. Jackson
26 Reporting Practices in Confirmatory Factor Analysis: An Overview and Some Recommendations
257(30)
Dennis L. Jackson
J. Arthur Gillaspy, Jr.
Rebecca Pure-Stephenson
27 Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review
287(26)
James B. Schreiber
Frances K. Stage
Jamie King
Amaury Nora
Elizabeth A. Barlow
6 Exploratory versus Confirmatory Factor Analysis
28 Factor Analysis in Counseling Psychology Research, Training, and Practice: Principles, Advances, and Applications
313(32)
Jeffrey H. Kahn
29 Exploratory and Confirmatory Factor Analysis: Guidelines, Issues, and Alternatives
345(20)
Amy E. Hurley
Terri A. Scandura
Chester A. Schriesheim
Michael T. Brannick
Anson Seers
Robert J. Vandenberg
Larry J. Williams
30 Current Methodological Considerations in Exploratory and Confirmatory Factor Analysis
365(22)
Thomas A. Schmitt
31 Comparing Exploratory and Confirmatory Factor Analysis: A Study on the 5-Factor Model of Personality
387(16)
Peter Borkenau
Fritz Ostendorf
32 In Search of Underlying Dimensions: The Use (and Abuse) of Factor Analysis in Personality and Social Psychology Bulletin
403
Daniel W. Russell
Volume III Alternative Approaches to Latent Variables
7 Principal Components Analysis
33 Component Analysis versus Common Factor Analysis: Some Issues in Selecting an Appropriate Procedure
3(26)
Wayne F. Velicer
Douglas N. Jackson
34 Component Analysis versus Common Factor Analysis: A Monte Carlo Study
29(14)
Steven C. Snook
Richard L. Gorsuch
35 Common Factor Analysis versus Principal Component Analysis: Differential Bias in Representing Model Parameters?
43(42)
Keith F. Widaman
36 Constructing Socio-Economic Status Indices: How to Use Principal Components Analysis
85(20)
Seema Vyas
Lilani Kumaranayake
8 Formative Measurement
37 Index Construction with Formative Indicators: An Alternative to Scale Development
105(18)
Adamantios Diamantopoulos
Heidi M. Winklhofer
38 A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research
123(32)
Cheryl Burke Jarvis
Scott B. MacKenzie
Philip M. Podsakoff
39 Interpretation of Formative Measurement in Information Systems Research
155(28)
Ronald T. Cenfetelli
Genevieve Bassellier
40 Advancing Formative Measurement Models
183(30)
Adamantios Diamantopoulos
Petra Riefler
Katharina P. Roth
41 The Error Term in Formative Measurement Models: Interpretation and Modeling Implications
213(12)
Adamantios Diamantopoulos
42 Questions about Formative Measurement
225(20)
James B. Wilcox
Roy D. Howell
Einar Breivik
43 Formative Measurement and Academic Research: In Search of Measurement Theory
245(28)
Andrew M. Hardin
Jerry Cha-Jan Chang
Mark A. Fuller
Gholamreza Torkzadeh
9 Formative versus Reflective Measurement
44 On the Nature and Direction of Relationships between Constructs and Measures
273(32)
Jeffrey R. Edwards
Richard P. Bagozzi
45 Reconsidering Formative Measurement
305(24)
Roy D. Howell
Einar Breivik
James B. Wilcox
46 Interpretational Confounding Is Due to Misspecification, Not to Type of Indicator: Comment on Howell, Breivik, and Wilcox (2007)
329(18)
Kenneth A. Bollen
47 On the Meaning of Formative Measurement and How It Differs from Reflective Measurement: Comment on Howell, Breivik, and Wilcox (2007)
347(16)
Richard P. Bagozzi
48 Is Formative Measurement Really Measurement? Reply to Bollen (2007) and Bagozzi (2007)
363(16)
Roy D. Howell
Einar Breivik
James B. Wilcox
49 The Fallacy of Formative Measurement
379
Jeffrey R. Edwards
Volume IV Advanced Topics
10 Factor Analysis with Ordinal and Dichotomous Data
50 An Empirical Evaluation of Alternative Methods of Estimation for Confirmatory Factor Analysis with Ordinal Data
3(38)
David B. Flora
Patrick J. Curran
51 Evaluating Estimation Methods for Ordinal Data in Structural Equation Modeling
41(16)
Pui-Wa Lei
52 The Sensitivity of Confirmatory Maximum Likelihood Factor Analysis to Violations of Measurement Scale and Distributional Assumptions
57(12)
Emin Babakus
Carl E. Ferguson, Jr.
Karl G. Joreskog
53 Polychoric versus Pearson Correlations in Exploratory and Confirmatory Factor Analysis of Ordinal Variables
69(18)
Francisco Pablo Holgado-Tello
Salvador Chacon-Moscoso
Isabel Barbero-Garcia
Enrique Vila-Abad
11 Factor Rotations
54 Rotations
87(8)
Herve Abdi
55 The Invariance Problem in Factor Analysis
95(8)
J.P. Guilford
56 Rotation Criteria and Hypothesis Testing for Exploratory Factor Analysis: Implications for Factor Pattern Loadings and Interfactor Correlations
103(20)
Thomas A. Schmitt
Daniel A. Sass
57 A Comparison of Factor Rotation Methods for Dichotomous Data
123(24)
W. Holmes Finch
12 Latent Class Analysis
58 Searching for Ideal Types: The Potentialities of Latent Class Analysis
147(22)
Jacques A. Hagenaars
Loek C. Halman
59 Latent Class Models in Social Work
169(14)
Susan Neely-Barnes
60 Identifying Class Structure: A Latent Class Analysis of the Criterion-Related and Construct Validity of the Goldthorpe Class Schema
183(26)
Geoffrey Evans
Colin Mills
61 Integrating Person-Centered and Variable-Centered Analyses: Growth Mixture Modeling with Latent Trajectory Classes
209(20)
Bengt Muthen
Linda K. Muthen
62 The Integration of Continuous and Discrete Latent Variable Models: Potential Problems and Promising Opportunities
229
Daniel J. Bauer
Patrick J. Curran
Salvatore J. Babones is a senior lecturer in sociology and social policy at the University of Sydney and an associate fellow at the Institute for Policy Studies (IPS). Previously, he was an assistant professor of sociology, public health, and public and international affairs at the University of Pittsburgh. He holds both a PhD in sociology and an MSE in mathematical sciences from the Johns Hopkins University. Dr. Babones is the author or editor of eight books and more than thirty academic papers. He is the editor of Applied Statistical Modeling and Fundamentals of Regression Modeling, both published by SAGE as part of the Benchmarks in Social Research Methods reference series. His academic research focuses on globalization, economic development, and statistical methods for comparative social science research.