Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English German |
| Published: |
New York, NY [u.a.]
Guilford Press
2011
|
| Series: | Methodology in the social sciences
|
| Subjects: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026034680&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026034680&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| Physical Description: | XIII, 305 S. Ill., graph. Darst. |
| ISBN: | 9781462502455 9781462507825 |
Staff View
MARC
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Record in the Search Index
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|---|---|
| adam_text | DATA ANALYSIS WITH MPLUS
Christian
Geiser
This text combines an extensive tutorial in Mplus programming with clear descriptions of the
statistical models being implemented. Coverage includes standard path and factor analytic
models, as well as longitudinal, multilevel, and latent class models. Many real examples are
analyzed throughout the book, with careful explanations of syntax, screen shots to help navigate
the program, and thorough discussions of results.
—
Roger E. Millsap,
Department of Psychology, Arizona State University
Mplus is arguably the most flexible commercially available software program for
SEM
and all of
its special cases.
Geiser
has provided an admirable service to the community of researchers who use
Mplus with this highly readable book. The book is an indispensable companion to more advanced
SEM
texts and is certainly an important supplementary text for graduate courses on
SEM.
—
David Kaplan,
Department of Educational Psychology, University of Wisconsin-Madison
More and more researchers all over the world are using Mplus. I know of no other book that
provides such a truly helpful tutorial on everything from the very first steps to how to run
complicated
SEM
models like latent growth models....Many easy-to-make mistakes can be
prevented by keeping this book within arm s reach.
—Rens
van
de Schoot,
Department of Methods and Statistics, Utrecht University, The Netherlands
A PRACTICAL INTRODUCTION TO USING MPLUS FOR THE ANALYSIS OF MULTIVARIATE DATA, THIS
volume provides step-by-step guidance, complete with real data examples, numerous screen
shots, and output excerpts. The author shows how to prepare a data set for import in Mplus
using SPSS. He explains how to specify different types of models in Mplus syntax and address
typical caveats
—
for example, assessing measurement
invariance
in longitudinal SEMs. Coverage
includes path and factor analytic models as well as mediational, longitudinal, multilevel, and
latent class models. Specific programming tips and solution strategies are presented in boxes
in each chapter. The companion website {http-.llcrmda.ku.edulguilfordlgeiser) features data sets,
annotated syntax files, and output for all of the examples. Of special utility to instructors and
students, many of the examples can be run with the free demo version of Mplus.
Contents
1 · Data Management in SPSS 1
1.1
Coding Missing Values
2
1.2
Exporting
an ASCII Data
File for Mplus
7
2 ·
Reading Data into Mplus
9
2.1
Importing and Analyzing Individual Data
(Raw Data)
10
2.1.1
Basic Structure of the Mplus Syntax
and BASIC Analysis
10
2.1.2
Mplus Output for BASIC Analysis
14
2.2
Importing and Analyzing Summary Data
(Covariance or Correlation Matrices)
21
3 ·
Linear Structural Equation Models
24
3.1
What Are Linear SEMs?
24
3.2
Simple Linear Regression Analysis
with Manifest Variables
28
3.3
Latent Regression Analysis
39
3.4
Confirmatory Factor Analysis
51
3.4.1
First-Order
CFA
51
3.4.2
Second-Order
CFA
58
3.5
Path Models and Mediator Analysis
62
3.5.1
Introduction and Manifest Path Analysis
62
3.5.2
Manifest Path Analysis in Mplus
65
3.5.3
Latent Path Analysis
73
3.5.4
Latent Path Analysis in Mplus
74
xi
хм
Contents
4 ·
Structural Equation Models
б
1
for Measuring Variability and Change
4.1
LS Analysis
82
4.1.1
LS versus LST Models
85
4.1.2
Analysis of LS Models in Mplus
85
4.1.3
Modeling Indicator-Specific Effects
88
4.1.4
Testing for Measurement
Invariance
across Time
99
4.2
LST Analysis
116
4.3
Autoregressive
Models
126
4.3.1
Manifest
Autoregressive
Models
127
4.3.2
Latent
Autoregressive
Models
133
4.4
Latent Change Models
145
4.5
Latent Growth Curve Models
163
4.5.1
First-Order LGCMs
164
4.5.2
Second-Order LGCMs
183
5 ·
Multilevel Regression Analysis
195
5.1
Introduction to Multilevel Analysis
195
5.2
Specification of Multilevel Models in Mplus
197
5.3
Option TwoLevel BASIC
198
5.4
Random Intercept Models
205
5.4.1
Null Model (Intercept-Only Model)
205
5.4.2
One-Way Random Effects ANCOVA
209
5.4.3
Means-as-Outcomes Model
214
5.5
Random Intercept and Slope Models
220
5.5.1
Random Coefficient Regression Analysis
221
5.5.2
Intercepts-and-Slopes-as-Outcomes Model
224
6 ·
Latent Class Analysis
232
6.1
Introduction to Latent Class Analysis
232
6.2
Specification of LCA Models in Mplus
235
6.3
Model Fit Assessment and Model Comparisons
257
6.3.1
Absolute Model Fit
258
6.3.2
Relative Model Fit
263
6.3.3
Interpretability
268
Appendix A. Summary of Key Mplus Commands
271
Discussed in This Book
Appendix B. Common Mistakes in the Mplus
279
Input Setup and Troubleshooting
Appendix C. Further Readings
283
Contents xiii
References
285
Author Index
293
Subject Index
296
About the Author
305
The companion website http://crmda.ku.edu/guilford/geiser provides
all data sets and Mplus input and output files, as well as additional
materials discussed in this book.
|
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| id | DE-604.BV041057474 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T16:29:50Z |
| institution | BVB |
| isbn | 9781462502455 9781462507825 |
| language | English German |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-026034680 |
| oclc_num | 854718861 |
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| physical | XIII, 305 S. Ill., graph. Darst. |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | Guilford Press |
| record_format | marc |
| series2 | Methodology in the social sciences |
| spellingShingle | Geiser, Christian 1978- Data analysis with Mplus Mplus (DE-588)7716737-5 gnd |
| subject_GND | (DE-588)7716737-5 |
| title | Data analysis with Mplus |
| title_alt | Datenanalyse mit Mplus |
| title_auth | Data analysis with Mplus |
| title_exact_search | Data analysis with Mplus |
| title_full | Data analysis with Mplus Christian Geiser |
| title_fullStr | Data analysis with Mplus Christian Geiser |
| title_full_unstemmed | Data analysis with Mplus Christian Geiser |
| title_short | Data analysis with Mplus |
| title_sort | data analysis with mplus |
| topic | Mplus (DE-588)7716737-5 gnd |
| topic_facet | Mplus |
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