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Applied Structural Equation Modeling using AMOS: Basic to Advanced Techniques [Mīkstie vāki]

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  • Formāts: Paperback / softback, 354 pages, height x width: 254x178 mm, weight: 635 g, 11 Tables, black and white; 26 Line drawings, black and white; 503 Halftones, black and white; 529 Illustrations, black and white
  • Izdošanas datums: 03-Jun-2020
  • Izdevniecība: Routledge
  • ISBN-10: 0367435268
  • ISBN-13: 9780367435264
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Applied Structural Equation Modeling using AMOS: Basic to Advanced TechniquesPalielināt
  • Formāts: Paperback / softback, 354 pages, height x width: 254x178 mm, weight: 635 g, 11 Tables, black and white; 26 Line drawings, black and white; 503 Halftones, black and white; 529 Illustrations, black and white
  • Izdošanas datums: 03-Jun-2020
  • Izdevniecība: Routledge
  • ISBN-10: 0367435268
  • ISBN-13: 9780367435264
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9780367435264.html
Keywords:

This is an essential how-to guide on the application of structural equation modeling (SEM) techniques with the AMOS software, focusing on the practical applications of both simple and advanced topics.

Written in an easy-to-understand conversational style, the book covers everything from data collection and screening to confirmatory factor analysis, structural model analysis, mediation, moderation, and more advanced topics such as mixture modeling, censored date, and non-recursive models. Through step-by-step instructions, screen shots, and suggested guidelines for reporting, Collier cuts through abstract definitional perspectives to give insight on how to actually run analysis. Unlike other SEM books, the examples used will often start in SPSS and then transition to AMOS so that the reader can have full confidence in running the analysis from beginning to end. Best practices are also included on topics like how to determine if your SEM model is formative or reflective, making it not just an explanation of SEM topics, but a guide for researchers on how to develop a strong methodology while studying their respective phenomenon of interest.

With a focus on practical applications of both basic and advanced topics, and with detailed work-through examples throughout, this book is ideal for experienced researchers and beginners across the behavioral and social sciences.

Recenzijas

This is one of the best book on Statistics and Research Methods I have ever reviewed so far. This book covers all you need to know on SEM i.e., the concept, introduction to the software, how to prepare data in SPSS and AMOS for analysis, measurement and structural elements of latent variable modelling, full SEM, mediation & moderation with latent variables, and latent growth analysis. To my knowledge, this is the most comprehensive book on the market. I highly recommend this book and I will definitely recommend it to all my students (undergraduate and postgraduate). -- Daniel Boduszek, University of Huddersfield, UK & SWPS University, Poland

Preface ix
Acknowledgments xi
1 Introduction to Structural Equation Modeling
1(16)
What Is Structural Equation Modeling?
1(1)
Basics of SEM Input: The Covariance Matrix
2(2)
Correlations Between Constructs
4(2)
Is SEM Causal Modeling?
6(1)
A Confirmatory Approach to SEM
7(1)
Theory Should Lead Conceptualization
8(1)
Assumptions of SEM
8(1)
SEM Software
9(1)
Understanding Diagram Symbols
9(2)
Independent vs. Dependent Latent Variables
11(1)
How to Measure an Unobserved Construct
11(2)
Greek Notation and SEM
13(4)
2 Data Screening, Assessing Reliability, Validity, and Identification
17(19)
Data Screening
17(2)
Screening for Impermissible Values in the Data
19(2)
How Do I Assess If I Have Missing Data?
21(2)
How Do I Address Missing Data?
23(2)
Assessing Reliability
25(4)
Identification With SEM Models
29(1)
How Do I Calculate the Degrees of Freedom?
30(2)
What Do I Do if My Model Is Under-Identified?
32(1)
Sample Size: How Much Is Enough?
33(1)
Understanding the Validity of Measures
33(3)
3 Understanding the AMOS Program
36(26)
Overview of the AMOS Graphics Window
36(2)
AMOS Functions Listed as Icons in Pinned Ribbon
38(15)
Tips to Using AMOS More Efficiently
53(6)
Quick Reference to AMOS Functions
59(3)
4 Measurement Model Analysis
62(66)
Introduction to Confirmatory Factor Analysis
62(1)
How Is a CFA Different From an EFA?
63(1)
Interpretation of Factor Loadings
64(1)
Setting the Metric
65(1)
Model Fit and Fit Statistics
65(3)
Modification Indices
68(3)
CFA Example in AMOS
71(12)
Assessing Convergent and Discriminant Validity of Your Measures
83(4)
If I Have a Weak Factor Loading, Should 1 Drop It?
87(1)
How to Calculate Composite Reliability
87(1)
What If I Have a Standardized Factor Loading Greater Than 1?
88(1)
How Do I Report My CFA Results?
89(1)
Measurement Model Invariance Across Groups
90(8)
Full vs. Partial Metric Invariance
98(1)
How Do I Know Which Parameter to Free in a Partial Invariance Test?
98(4)
Common Method Bias
102(6)
What If My Test for Common Method Bias Is Significant?
108(1)
What if My Common Method Bias Test Is Non-Significant?
109(1)
What Is a Second Order Confirmatory Factor Analysis Model?
109(1)
Reflective vs. Formative Indicators
110(3)
Potential Identification Problems With Formative Indicators
113(2)
Dependent Relationships With Formative Constructs
115(1)
Higher Order Formative Construct Example
116(6)
How Do I Present the Result of My Higher Order Formative Model?
122(1)
Error Messages in AMOS
122(6)
5 Path and Full Structural Models
128(42)
Path Analysis
128(5)
Can I Use a Correlation Matrix as My Data Input?
133(4)
Full Structural Model Analysis
137(5)
How Do I Report My Full Structural Model Results?
142(1)
Using Specification Search to Aid in Model Trimming and Fit
143(3)
What Are Alternative Models, and Why Should I Be Concerned With Them?
146(1)
How Do I Add a Control Variable to My Structural Model?
147(2)
Two Group Analysis
149(12)
What if I Have More Than Two Groups in My Analysis?
161(1)
When I Try to Run My Structural Analysis, I Get an Error Message About My Matrix Not Being Positive Definite
161(1)
Can I Correlate the Error Terms of Two Unobservable Constructs in a Full Structural Model?
162(1)
How Do I Present the Results of My Two Group Analysis?
162(1)
How Do I Search for Multivariate Outliers?
162(3)
How Do 1 Determine if My Data Is Not Normally Distributed (Non-Normal)?
165(1)
What if I Get an Error Message in the Analysis That Says "Iteration Limit Reached"?
166(4)
6 Mediation
170(27)
Introduction to Mediation
170(2)
How to Test for Mediation
172(8)
How Do I Report the Results of My Mediation Test?
180(1)
Can I Use a Correlation Matrix or Summary Data to Test Mediation in AMOS?
181(1)
What if I Have Multiple Mediators in My Model?
182(6)
How Do I Test Serial Mediation?
188(6)
Setting the Seed in Bootstrapping
194(3)
7 Moderation
197(43)
Introduction to Moderation
197(5)
Probing the Interaction
202(5)
Testing Moderation in a Full Structural Model
207(12)
How Do I Present My Moderation Results?
219(2)
Mean Center vs. Z Score in Moderation Testing
221(2)
Moderation Testing With a Categorical Moderator
223(4)
Calculating Categorical Moderation via Pairwise Parameter Comparison
227(2)
Moderated Mediation With a Continuous Moderator
229(5)
How Do I Report the Results of My Moderated Mediation Test?
234(1)
Moderated Mediation With a Categorical Moderator
234(6)
8 Using Categorical Independent Variables in SEM
240(20)
Binary Categorical Variables in SEM
240(2)
Mediation with Binary Categorical Independent Variables
242(2)
Multicategorical Independent Variables in SEM
244(3)
Mediation With Multicategorical Independent Variables
247(4)
Moderated Mediation With a Multicategorical Independent Variable
251(5)
How Do I Report the Results of My Multicategorical Moderated Mediation Test?
256(4)
9 Latent Growth Curve Models
260(22)
Introduction to Latent Growth Curve Models
260(9)
Including Predictors Into a Latent Growth Curve Model
269(4)
How Do I Present My Latent Growth Curve Results?
273(1)
Latent Growth Curves With Nonlinear Patterns
274(3)
Latent Growth Curves Across Two Domains
277(5)
10 Advanced Topics in SEM
282(65)
Using Weighted Scores in AMOS
282(5)
How to Use Bootstrapping to Account for Non-Normal Data
287(6)
Mixture Modeling
293(9)
Analyzing Censored Data
302(8)
Non-Recursive Models (Feedback Loops)
310(7)
Post-Hoc Power Analysis
317(1)
Using Specification Search to Perform Exploratory Factor Analysis
317(6)
How to Use Plugins to Create a Model Instead of Drawing a Model in AMOS
323(15)
How to Use the Program Editor to Conceptualize Your Model and Run the Analysis
338(9)
Appendix: Table of Chi-Square Statistics 347(1)
Index 348
Joel E. Collier Ph.D. is the Tommy and Terri Nusz Professor of Marketing at Mississippi State University, USA. He is also the Ph.D. Director for doctoral studies in the Department of Marketing. Dr. Collier teaches structural equation modeling on the doctoral level and has published numerous articles in the top journals of his field using this technique. He has also worked as a consultant for the following firms: Time Warner, Muvico, Reeds Jewelers, Cashman Photo, and the Carolina Hurricanes professional hockey team.