HLM 6: hierarchical linear and nonlinear modeling
Saved in:
| Format: | Book |
|---|---|
| Language: | English |
| Published: |
Lincolnwood, Ill.
Scientific Software International
2005
|
| Edition: | 2. print. with revisions |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis Klappentext |
| Physical Description: | 297, [9] S. Ill., graph. Darst. |
| ISBN: | 0894980548 |
Staff View
MARC
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Record in the Search Index
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|---|---|
| adam_text | Contents
Conceptual
1.1
1.1.1
1.1.2
1.2
1.3
1.4
1.5
level
1.6
1.7
1.8
1.9
Working with HLM2
2.1
2.2
2.3
2.4
2.5
2.5.1
2.5.2
2.5.3
2.5.4
2.6
2.7
2.8
2.8.1
2.8.2
2.8.3
2.8.4
2.8.5
2.8.6
2.8.7
2.8.8
2.9
2.10
2.11
2.12
3
3.1
3.1.1
3.1.2
3.1.3
3.2
3.3
4
4.1
4.1.1
4.2
4.2.1
4.3
4.4
4.5
4.5.1
4.5.2
4.5.3
4.5.4
4.5.5
5
Linear Models (HGLM)
5.1
5.1.1
5.1.2
5.1.3
5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.4
5.4.1
5.4.2
5.4.3
5.4.4
5.5
5.5.1
5.5.2
5.6
5.6.1
5.6.2
5.6.3
5.7
5.8
5.9
5.10
6
6.1
6.2
6.3
6.4
6.5
6.6
6.7
6.8
6.8.1
6.8.2
6.8.3
6.9
7
Linear Models (HMLM)
7.1
7.1.1
7.1.2
7.1.3
7.2
7.2.1
7.2.2
7.2.3
7.3
7.4
7.5
7.6
7.6.1
7.6.2
7.6.3
7.6.4
8
8.1
8.1.1
8.2
8.3
8.4
8.5
9 Special Features......................................................................................173
9.1 Latent variable
9.1.1
9.1.2
9.2
9.2.1
9.2.2
9.2.3
9.2.4
9.3
9.3.1
9.3.2
9.3.3
9.3.4
10
Effect Models (HCM2)
10.1
10.1.1
10.1.2
10.2
10.3
11
11.1
11.1.1
11.1.2
11.1.3
11.1.4
11.2
11.3
predictor fixed
11.4
12
12.1
12.1.1
12.1.2
12.1.3
12.2
12.2.1
12.2.2
12.2.3
12.2.4
12.2.5
12.2.6
12.3
A Using
A.1 Using HLM2 in interactive mode
A.1
A.1.2 Example: constructing an MDM file for the HS&B data using ASCII file Input
A.2 Rules for format statements
A.2.1 Example: Executing an analysis using HSB.MDM
A.3 Using HLM in batch and/or interactive mode
A.4 Using HLM2 in batch mode
A.5 Printing of variance and covariance matrices for fixed effects and level-2 variances
A.6 Preliminary exploratory analysis with HLM2
B Using HLM3 in Interactive and Batch Mode
B.1 Using HLM3 in interactive mode
B,1
B.1
B.1.3 Example: Executing an analysis using EG.MDM
B.2 Using HLM3 in batch mode
B.2.1 Table of keywords and options
B.3 Printing of variance and covariance matrices
C Using HGLM in Interactive and Batch Mode
C.1 Example: Executing an analysis using THAIUGRP.MDM
D Using
D.1 Constructing an MDM file
D.2 Executing analyses based on MDM files
D.2.1 Table of keywords and options
D.2.2 Table of HMLM2 keywords and options
E
E.1 Example: Latent variable analysis using the National Youth Study data sets
E.2 A latent variable analysis to run regression with missing data
E.3 Commands to apply HLM to multiply-imputed data
F
F.1 Using HCM2 in interactive mode
F.1.1 Example: constructing an MDM file for the educational attainment data as described in Chapter
using SPSS file input
F.1.2 Example: Executing an unconditional model analysis using ATTAIN.MDM
F.1.3 Example: Executing a conditional model analysis using ATTAIN.MDM
F.2 Using HCM2 in batch mode
References
Subject Index
New in this version:
Model equations displayed in
hierarchical or mixed-model
format with or without
subscripts
publication. Distributional
assumptions and link functions
are presented in detail.
Cross-classified random effects
models for linear models and
non-linear link functions with
convenient Windows interface
High-order Laplace approxi¬
mation with EM algorithm
for stable convergence and
accurate estimation in two-
level hierarchical generalized
linear models (HGLM)
New flexible and accurate
sample design weighting for
two- and three-level HLMs
and HGLMs
Easier automated input from
a wide variety of software
packages, including the
current versions of
and
Residual files can be saved
directly as SPSS (sav) files
Completely revised manual and
online Help documentation
Analyses are based! on MDM
files, replacing the older, less
flexible SSM format
AH new
graphical displays of data:
Group-specific scatter plots, line
plots, and cubic splines that can
be color coded by values of
predictor variables; box-plots
displayed for overall data and
data grouped within higher-
level units.
Greatly expanded graphics
for fitted models:
Graphing of group-specific
equations, box-plots of level-1
residuals for each group, plots
of residuals by predicted values
for each group, posterior
credibility intervals for random
coefficients. For three-level
models, level-1 trajectories are
displayed in separate graphs or
grouped by level-3 unit. Graphs
can be color coded by values of
predictor variables.
|
| adam_txt |
Contents
Conceptual
1.1
1.1.1
1.1.2
1.2
1.3
1.4
1.5
level
1.6
1.7
1.8
1.9
Working with HLM2
2.1
2.2
2.3
2.4
2.5
2.5.1
2.5.2
2.5.3
2.5.4
2.6
2.7
2.8
2.8.1
2.8.2
2.8.3
2.8.4
2.8.5
2.8.6
2.8.7
2.8.8
2.9
2.10
2.11
2.12
3
3.1
3.1.1
3.1.2
3.1.3
3.2
3.3
4
4.1
4.1.1
4.2
4.2.1
4.3
4.4
4.5
4.5.1
4.5.2
4.5.3
4.5.4
4.5.5
5
Linear Models (HGLM)
5.1
5.1.1
5.1.2
5.1.3
5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.4
5.4.1
5.4.2
5.4.3
5.4.4
5.5
5.5.1
5.5.2
5.6
5.6.1
5.6.2
5.6.3
5.7
5.8
5.9
5.10
6
6.1
6.2
6.3
6.4
6.5
6.6
6.7
6.8
6.8.1
6.8.2
6.8.3
6.9
7
Linear Models (HMLM)
7.1
7.1.1
7.1.2
7.1.3
7.2
7.2.1
7.2.2
7.2.3
7.3
7.4
7.5
7.6
7.6.1
7.6.2
7.6.3
7.6.4
8
8.1
8.1.1
8.2
8.3
8.4
8.5
9 Special Features.173
9.1 Latent variable
9.1.1
9.1.2
9.2
9.2.1
9.2.2
9.2.3
9.2.4
9.3
9.3.1
9.3.2
9.3.3
9.3.4
10
Effect Models (HCM2)
10.1
10.1.1
10.1.2
10.2
10.3
11
11.1
11.1.1
11.1.2
11.1.3
11.1.4
11.2
11.3
predictor fixed
11.4
12
12.1
12.1.1
12.1.2
12.1.3
12.2
12.2.1
12.2.2
12.2.3
12.2.4
12.2.5
12.2.6
12.3
A Using
A.1 Using HLM2 in interactive mode
A.1
A.1.2 Example: constructing an MDM file for the HS&B data using ASCII file Input
A.2 Rules for format statements
A.2.1 Example: Executing an analysis using HSB.MDM
A.3 Using HLM in batch and/or interactive mode
A.4 Using HLM2 in batch mode
A.5 Printing of variance and covariance matrices for fixed effects and level-2 variances
A.6 Preliminary exploratory analysis with HLM2
B Using HLM3 in Interactive and Batch Mode
B.1 Using HLM3 in interactive mode
B,1
B.1
B.1.3 Example: Executing an analysis using EG.MDM
B.2 Using HLM3 in batch mode
B.2.1 Table of keywords and options
B.3 Printing of variance and covariance matrices
C Using HGLM in Interactive and Batch Mode
C.1 Example: Executing an analysis using THAIUGRP.MDM
D Using
D.1 Constructing an MDM file
D.2 Executing analyses based on MDM files
D.2.1 Table of keywords and options
D.2.2 Table of HMLM2 keywords and options
E
E.1 Example: Latent variable analysis using the National Youth Study data sets
E.2 A latent variable analysis to run regression with missing data
E.3 Commands to apply HLM to multiply-imputed data
F
F.1 Using HCM2 in interactive mode
F.1.1 Example: constructing an MDM file for the educational attainment data as described in Chapter
using SPSS file input
F.1.2 Example: Executing an unconditional model analysis using ATTAIN.MDM
F.1.3 Example: Executing a conditional model analysis using ATTAIN.MDM
F.2 Using HCM2 in batch mode
References
Subject Index
New in this version:
Model equations displayed in
hierarchical or mixed-model
format with or without
subscripts
publication. Distributional
assumptions and link functions
are presented in detail.
Cross-classified random effects
models for linear models and
non-linear link functions with
convenient Windows interface
High-order Laplace approxi¬
mation with EM algorithm
for stable convergence and
accurate estimation in two-
level hierarchical generalized
linear models (HGLM)
New flexible and accurate
sample design weighting for
two- and three-level HLMs
and HGLMs
Easier automated input from
a wide variety of software
packages, including the
current versions of
and
Residual files can be saved
directly as SPSS (sav) files
Completely revised manual and
online Help documentation
Analyses are based! on MDM
files, replacing the older, less
flexible SSM format
AH new
graphical displays of data:
Group-specific scatter plots, line
plots, and cubic splines that can
be color coded by values of
predictor variables; box-plots
displayed for overall data and
data grouped within higher-
level units.
Greatly expanded graphics
for fitted models:
Graphing of group-specific
equations, box-plots of level-1
residuals for each group, plots
of residuals by predicted values
for each group, posterior
credibility intervals for random
coefficients. For three-level
models, level-1 trajectories are
displayed in separate graphs or
grouped by level-3 unit. Graphs
can be color coded by values of
predictor variables. |
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| id | DE-604.BV020834928 |
| illustrated | Illustrated |
| index_date | 2024-07-02T13:14:36Z |
| indexdate | 2024-07-09T20:26:13Z |
| institution | BVB |
| isbn | 0894980548 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014156887 |
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| physical | 297, [9] S. Ill., graph. Darst. |
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| publisher | Scientific Software International |
| record_format | marc |
| spelling | HLM 6 hierarchical linear and nonlinear modeling [Stephen W. Raudenbush ...] 2. print. with revisions Lincolnwood, Ill. Scientific Software International 2005 297, [9] S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Datenanalyse Methode Sozialwissenschaften Lineares Modell - Empirische Sozialforschung Lineares Modell - Hierarchisches System Lineares Modell (DE-588)4134827-8 gnd rswk-swf Software (DE-588)4055382-6 gnd rswk-swf Lineares Modell (DE-588)4134827-8 s Software (DE-588)4055382-6 s DE-604 Raudenbush, Stephen W. Sonstige oth Digitalisierung UBPassau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014156887&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014156887&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | HLM 6 hierarchical linear and nonlinear modeling Datenanalyse Methode Sozialwissenschaften Lineares Modell - Empirische Sozialforschung Lineares Modell - Hierarchisches System Lineares Modell (DE-588)4134827-8 gnd Software (DE-588)4055382-6 gnd |
| subject_GND | (DE-588)4134827-8 (DE-588)4055382-6 |
| title | HLM 6 hierarchical linear and nonlinear modeling |
| title_auth | HLM 6 hierarchical linear and nonlinear modeling |
| title_exact_search | HLM 6 hierarchical linear and nonlinear modeling |
| title_exact_search_txtP | HLM 6 hierarchical linear and nonlinear modeling |
| title_full | HLM 6 hierarchical linear and nonlinear modeling [Stephen W. Raudenbush ...] |
| title_fullStr | HLM 6 hierarchical linear and nonlinear modeling [Stephen W. Raudenbush ...] |
| title_full_unstemmed | HLM 6 hierarchical linear and nonlinear modeling [Stephen W. Raudenbush ...] |
| title_short | HLM 6 |
| title_sort | hlm 6 hierarchical linear and nonlinear modeling |
| title_sub | hierarchical linear and nonlinear modeling |
| topic | Datenanalyse Methode Sozialwissenschaften Lineares Modell - Empirische Sozialforschung Lineares Modell - Hierarchisches System Lineares Modell (DE-588)4134827-8 gnd Software (DE-588)4055382-6 gnd |
| topic_facet | Datenanalyse Methode Sozialwissenschaften Lineares Modell - Empirische Sozialforschung Lineares Modell - Hierarchisches System Lineares Modell Software |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014156887&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=014156887&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT raudenbushstephenw hlm6hierarchicallinearandnonlinearmodeling |