Multilevel and longitudinal modeling with IBM SPSS:
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
New York [u.a.]
Routledge
2010
|
| Schriftenreihe: | Quantitative methodology series
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020556667&sequence=000002&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=020556667&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XII, 343 S. Ill., graph. Darst. |
| ISBN: | 9781848728622 9781848728639 |
Internformat
MARC
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| 100 | 1 | |a Heck, Ronald H. |e Verfasser |0 (DE-588)14277250X |4 aut | |
| 245 | 1 | 0 | |a Multilevel and longitudinal modeling with IBM SPSS |c Ronald H. Heck ; Scott L. Thomas ; Lynn N. Tabata |
| 264 | 1 | |a New York [u.a.] |b Routledge |c 2010 | |
| 300 | |a XII, 343 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Quantitative methodology series | |
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| 689 | 0 | 1 | |a SPSS |0 (DE-588)4056588-9 |D s |
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| 700 | 1 | |a Thomas, Scott L. |e Verfasser |4 aut | |
| 700 | 1 | |a Tabata, Lynn N. |e Verfasser |4 aut | |
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Datensatz im Suchindex
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|---|---|
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| adam_text |
Contents
Preface
xi
Chapter
1
Introduction to Multilevel and Longitudinal Modeling With IBM SPSS
1
Our Intent
2
Analysis of Multilevel Data Structures
3
Partitioning Variation in an Outcome
6
What SPSS Can and Cannot Do
7
Developing a General Multilevel Modeling Strategy
9
Illustrating the Steps in Investigating a Proposed Model
9
One-Way ANOVA (No Predictors) Model
10
Analyze a Level
1
Model With Fixed Predictors
11
Add the Level
2
Explanatory Variables
12
Examine Whether a Particular Slope Coefficient Varies Between Groups
13
Adding Cross-Level Interactions to Explain Variation in the Slope
14
Syntax Versus SPSS Menu Command Formulation
16
Model Estimation and Other Typical Multilevel Modeling Issues
17
Sample Size
18
Power
18
Differences Between Multilevel Software Programs
19
A Note About Standardized and Unstandardized Coefficients
19
Summary
20
Chapter
2
Preparing and Examining the Data for Multilevel Analyses
21
Data Requirements
21
File Layout
22
Getting Familiar With Basic SPSS Data Commands
24
Recode:
Creating a New Variable Through Recoding
24
Compute: Creating a New Variable That is a Function of Some Other Variable
29
Match Files: Combining Data From Separate SPSS Files
30
Aggregate: Collapsing Data Within Level
2
Units
36
Varstocases: Vertical Versus Horizontal Data Structures
38
Using "Rank" to
Recode
the Level
1
or Level
2
Data for Nested Models
44
Creating an Identifier Variable
45
Creating an Individual-Level Identifier Using Compute
45
Creating a Group-Level Identifier Using Rank Cases
47
Creating a Within-Group-Level Identifier Using Rank Cases
49
Centering
51
Grand-Mean Centering
53
Group-Mean Centering
54
Checking the Data
58
A Note About Model Building
58
Summary
59
vi
■
Coniante
Chapter
3
Defining a Basic Two-Level Multilevel Regression Model
From Single-Level to Multilevel Analysis
Building a Two-Level Model
Research Questions
The Data
Graphing the Relationship Between
SES
and Math Test Scores With SPSS
Menu Commands
Graphing the Subgroup Relationships Between
SES
and Math Test Scores
With SPSS Menu Commands
Building a Multilevel Model With SPSS Mixed
Step
1:
Examining Variance Components Using the Null Model
Defining the Null Model With SPSS Menu Commands
Interpreting the Output From the Null Model
Step
2:
Building the Individual-Level (or Level
1)
Random Intercept Model
Model
1:
Defining the Level
1
Random Intercept Model With SPSS Menu
Commands
Interpreting the Output From Model
1
Step
3:
Building the Group-Level (or Level
2)
Random Intercept Model
Model
2:
Defining the Group-Level Random Intercept Model With SPSS
Menu Commands
Interpreting the Output From Model
2
Defining the Public School Variable as a Covariate Using SPSS Menu
Commands
Step
4:
Adding a Randomly Varying Slope (the Random Slope and Intercept
Model)
Model
3:
Defining the Random Slope and Intercept Model With SPSS Menu
Commands
Interpreting the Output From Model
3
Step
5:
Explaining Variability in the Random Slope (More Complex Random
Slopes and Intercept Models)
Model
4:
Defining More Complex Random Slope and Intercept Models With
SPSS Menu Commands
Interpreting the Output From Model
4
Graphing SES-Achievement Relationships in High- and Low-Achieving
Schools With SPSS Menu Commands
Summary
Chapter
4
Three-Level Univariate Regression Models
Three-Level Univariate Model
Research Questions
The Data
Defining the Three-Level Multilevel Model
Centering Predictors and Interactions
The Null Model (No Predictors)
Defining the Null Model (No Predictors) With SPSS Menu Commands
Interpreting the Output From the Null Model
Model
1:
Defining Predictors at Each Level
Defining Model
1
(Predictors at Each Level) With SPSS Menu Commands
Interpreting the Output From Model
1
61
61
63
63
64
65
70
72
73
74
78
80
81
83
86
87
89
91
93
95
97
98
99
104
106
110
111
111
111
112
112
113
115
115
120
121
122
124
Contents
vii
Model 2:
Group-Mean Centering
125
Defining Model
2
With SPSS Menu Commands
125
Interpreting the Output From Model
2 127
Covariance Estimates
128
Model
3:
Does the Slope Vary Randomly Across Classrooms and Schools?
129
Defining Model
3
With SPSS Menu Commands
130
Interpreting the Output From Model
3 132
Developing an Interaction Term
133
Preliminary Investigation of the Interaction
133
Model
4:
Examining a Level
2
Interaction
134
Defining Model
4
With SPSS Menu Commands
135
Interpreting the Output From Model
4 138
Comparing the Fit of Successive Models
139
Summary
140
Chapter
5
Examining Individual Change With Repeated Measures Data
141
An Example Study
141
Research Questions
142
Data
142
Univariate or Multivariate Approach
142
Examining the Shape of Students' Growth Trajectories
143
Graphing the Linear Growth Trajectories With SPSS Menu Commands
145
Examining Growth Trajectories Using Repeated Measures ANOVA
151
Conducting Repeated Measures ANOVA With SPSS Menu Commands
151
Interpreting the Output From the Repeated Measures ANOVA
154
Adding Between-Subjects Predictors
155
Adding Between-Subjects Predictors With SPSS Menu Commands
156
Interpreting the Output From Adding Between-Subjects Predictors
159
Using SPSS Mixed to Examine Individual Change
160
Developing a Two-Level Model of Individual Change
162
Level
1
Covariance Structure
162
Level
2
Covariance Structure
165
Model
1:
Does the Slope Vary Randomly Across Individuals?
165
Defining Model
1
With SPSS Menu Commands
166
Interpreting the Output From Model
1 169
Investigating Other Level
1
Covariance Structures
171
Investigating Other Level
1
Covariance Structures Using SPSS Menu
Commands
173
Model
2:
Adding the Between-Subjects Predictors
178
Defining Model
2
With SPSS Menu Commands
178
Interpreting the Output From Model
2 184
Graphing the Growth Rate Trajectories With SPSS Menu Commands
187
Summary
188
Chapter
6
Methods for Examining Organizational-Level Change
189
Examining Changes in Institutions' Graduation Rates
189
Research Questions
190
Data
191
viii
·
Conferite
191
Defining the Model 191
Level
1
Model 192
Level
2
Model
„„
Level3 Model
.
Null Model: No Predictors l^
Level
1
Error Structures
Defining the Null Model (No Predictors) With SPSS Menu Commands
196
Interpreting the Output From the Null Model 201
Model
1:
Adding Growth Rates 202
Level
1
Model
202
Coding the Time Variable 202
Defining Model
1
With SPSS Menu Commands
204
Interpreting the Output From Model
1
207
Model
2:
Adding Time-Varying Covariates
208
Defining Model
2
With SPSS Menu Commands
209
Interpreting the Output From Model
2 211
Model
3:
Explaining Differences in Growth Trajectories Between Institutions
211
Defining Model
3
With SPSS Menu Commands
212
Interpreting the Output From Model
3 216
Model
4:
Adding a Model to Examine Growth Rates at Level
3 217
Defining Model
4
With SPSS Menu Commands
218
Interpreting the Output From Model
4 221
Other Types of Random-Coefficients Growth Models
222
Summary
222
Chapter
7
Multivariate Multilevel Models
223
Multilevel Latent-Outcome Model
223
Research Questions
224
lhe
Data
224
Defining a Latent Variable for a Multilevel Analysis
226
Null Model: No Predictors
227
Defining the Null Model (No Predictors) With SPSS Menu Commands
229
Interpreting the Output of the Null Model
234
Model
1:
Building a Three-Level Model
234
Defining Model
1
With SPSS Menu Commands
235
Interpreting the Output of Model
1
(Explaining Student Achievement)
237
Model
2:
Investigating a Random Slope
238
Defining Model
2
With SPSS Menu Commands
238
Interpreting the Output of Model
2 241
Model
3:
Explaining Variation in Slopes
241
Defining Model
3
(Variation in Academic Achievement Slopes) With SPSS
Menu Commands
242
Interpreting the Output of Model
3 246
Comparing Model Estimates
246
Mukivariate Multilevel Model for Correlated Outcomes
247
The Data
247
Research Questions
248
Formulating the Basic Model
248
Null
Modei
(No Predictors)
249
Model
1:
Building a Complete Model (Predictors and Cross-Level Interactions)
262
Contents
ix
Testing
the Hypotheses
268
Covariance Components
268
Summary
270
Chapter
8
Cross-Classified Multilevel Models
271
Students Cross-Classified in High Schools and Universities
271
Research Questions
271
The Data
271
Descriptive Statistics
273
Defining Models in SPSS
274
Model
1:
Adding a Set of Level
1
and Level
2
Predictors
275
Defining Model
1
With SPSS Menu Commands
276
Interpreting the Output From Model
1 281
Model
2:
Investigating a Random Slope
282
Defining Model
2
With SPSS Menu Commands
282
Interpreting the Output From Model
2 286
Model
3:
Explaining Variation Between Variables
286
Defining Model
3
With SPSS Menu Commands
287
Interpreting the Output From Model
3 290
Developing a Cross-Classified Teacher Effectiveness Model
291
The Data Structure and Model
291
Research Questions
292
Model
1:
Intercept-Only Model
293
Defining Model
1
With SPSS Menu Commands
294
Model
2:
Defining the Cross-Classified Model With Previous Achievement
300
Defining Model
2
With SPSS Menu Commands
301
Interpreting the Output From Models
1
and
2 303
Model
3:
Adding Teacher Effectiveness and a Student Background Control
304
Defining Model
3
With SPSS Menu Commands
305
Interpreting the Output From Model
3 307
Model
4:
Adding a School-Level Predictor and a Random Slope
308
Defining Model
4
With SPSS Menu Commands
308
Interpreting the Output From Model
4 311
Model
5:
Examining Level
3
Differences Between Institutions
311
Defining Model
5
With SPSS Menu Commands
312
Interpreting the Output From Model
5 314
Model
6:
Adding a Level
3
Cross-Level Interaction
315
Defining Model
6
With SPSS Menu Commands
315
Interpreting the Output From Model
6 318
Summary
318
Chapter
9
Concluding Thoughts
319
References
323
Appendices
A: Syntax Statements
325
B: Model Comparisons Across Software Applications
335
Author Index
339
Subject Index
341
"With its thorough coverage of the statistical underpinnings of multilevel modeling and the detailed step-by-
;rep instructions on how to analyze data with IBM SPSS, this text is a gold mine for graduate instruction!"
-
Laura M.
Stapleton,
University of Maryland, Baltimore County, USA
"This text has both depth and breadth of coverage with material that is accessible and transparent to the novice
but at the same time comprehensive for the experienced researcher. It is one of those rare texts that is thorough
in both the how-tos of the software and the concepts. It is a key multilevel text that any multilevel researcher will
not want to be without."
-
Debbie L. Hahs-Vaughn, University of Central Florida, USA
"This book is a timely and valuable addition. Multilevel modeling is now becoming much more accessible to
oractitioners, many of whom use SPSS for other analyses. Therefore, a book like this [is] a great resource .I
would purchase the book and require it for my courses.
.
It is a unique contribution to a field.
.
I wish I would have
thought of writing it first!"
-
Dick Carpenter, University of Colorado, Colorado Springs, USA
"The first on the market to explain and illustrate how these multilevel models can be analyzed using the popular
SPSS program."
-
George Marcoulides, University of California
-
Riverside, USA
This is the first book to demonstrate how to use the multilevel and longitudinal modeling techniques available
in IBM SPSS Version
18.
The authors tap the power of SPSS's Mixed Models routine to provide an elegant
and accessible approach to these models. Readers who have learned statistics using this software will no
onger have to adapt to a new program to conduct quality multilevel and longitudinal analyses. Annotated
screen shots with all of the key output provide readers with a step-by-step understanding of each technique as
they are shown how to navigate through the program. Diagnostic tools, data management issues, and related
graphics are introduced throughout. SPSS commands show the flow of the menu structure and how to facilitate
model building. Annotated syntax is also available for those who prefer this approach. Most chapters feature an
extended example illustrating the logic of model development. These examples show readers the context and
'ationale of the research questions and the steps around which the analyses are structured. The data used in
:he text and syntax examples are available at www.psypress.com/multilevel-modeling-techniques.
The book opens with the conceptual and methodological issues associated with multilevel and longitudinal
modeling, followed by a discussion of SPSS data management techniques which facilitate working with
multilevel, longitudinal, and/or cross-classified data sets. The next few chapters introduce the basics of multilevel
modeling, how to develop a multilevel model, and trouble-shooting techniques for common programming and
nodeling problems along with potential solutions. Models for investigating individual and organizational change
ire developed in chapters
5
and
6,
followed by models with multivariate outcomes in chapter
7.
Chapter
8
llustrates SPSS's facility for examining models with cross-classified data structures. The book concludes with
houghts about ways to expand on the various multilevel and longitudinal modeling techniques introduced and
ssues to keep in mind in conducting multilevel analyses.
deal as a supplementary text for graduate level courses on multilevel, longitudinal, latent variable modeling,
nultivariate statistics, and/or advanced quantitative techniques taught in departments of psychology, business,
iducation, health, and sociology, this book's practical approach will also appeal to researchers in these fields.
rhe book provides an excellent supplement to Heck
&
Thomas's An Introduction to Multilevel Modeling
rechniques,
2nd
edition; however, it can also be used with any multilevel and/or longitudinal modeling book or
is a stand-alone text. |
| any_adam_object | 1 |
| author | Heck, Ronald H. Thomas, Scott L. Tabata, Lynn N. |
| author_GND | (DE-588)14277250X |
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| author_sort | Heck, Ronald H. |
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| building | Verbundindex |
| bvnumber | BV036636961 |
| classification_rvk | MR 2100 MR 2200 QH 230 ST 601 |
| classification_tum | SOZ 720f DAT 307f |
| ctrlnum | (OCoLC)699762912 (DE-599)BVBBV036636961 |
| discipline | Informatik Soziologie Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV036636961 |
| illustrated | Illustrated |
| indexdate | 2025-01-11T13:44:42Z |
| institution | BVB |
| isbn | 9781848728622 9781848728639 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-020556667 |
| oclc_num | 699762912 |
| open_access_boolean | |
| owner | DE-29 DE-20 DE-91 DE-BY-TUM DE-739 DE-188 DE-83 DE-11 DE-473 DE-BY-UBG DE-384 DE-19 DE-BY-UBM |
| owner_facet | DE-29 DE-20 DE-91 DE-BY-TUM DE-739 DE-188 DE-83 DE-11 DE-473 DE-BY-UBG DE-384 DE-19 DE-BY-UBM |
| physical | XII, 343 S. Ill., graph. Darst. |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | Routledge |
| record_format | marc |
| series2 | Quantitative methodology series |
| spellingShingle | Heck, Ronald H. Thomas, Scott L. Tabata, Lynn N. Multilevel and longitudinal modeling with IBM SPSS SPSS (DE-588)4056588-9 gnd Statistisches Modell (DE-588)4121722-6 gnd |
| subject_GND | (DE-588)4056588-9 (DE-588)4121722-6 |
| title | Multilevel and longitudinal modeling with IBM SPSS |
| title_auth | Multilevel and longitudinal modeling with IBM SPSS |
| title_exact_search | Multilevel and longitudinal modeling with IBM SPSS |
| title_full | Multilevel and longitudinal modeling with IBM SPSS Ronald H. Heck ; Scott L. Thomas ; Lynn N. Tabata |
| title_fullStr | Multilevel and longitudinal modeling with IBM SPSS Ronald H. Heck ; Scott L. Thomas ; Lynn N. Tabata |
| title_full_unstemmed | Multilevel and longitudinal modeling with IBM SPSS Ronald H. Heck ; Scott L. Thomas ; Lynn N. Tabata |
| title_short | Multilevel and longitudinal modeling with IBM SPSS |
| title_sort | multilevel and longitudinal modeling with ibm spss |
| topic | SPSS (DE-588)4056588-9 gnd Statistisches Modell (DE-588)4121722-6 gnd |
| topic_facet | SPSS Statistisches Modell |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020556667&sequence=000002&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=020556667&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT heckronaldh multilevelandlongitudinalmodelingwithibmspss AT thomasscottl multilevelandlongitudinalmodelingwithibmspss AT tabatalynnn multilevelandlongitudinalmodelingwithibmspss |
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Teilbibliothek Stammgelände
| Signatur: |
0002 DAT 307f 2011 B 74 Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |