HLM7: hierarchical linear and nonlinear modeling
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| Main Authors: | , , , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Skokie, IL
SSI, Scientific Software International
[2011]
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | 351 Seiten Illustrationen, Diagramme |
| ISBN: | 9780894980572 |
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MARC
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| 246 | 1 | 3 | |a HLM 7 |
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| 700 | 1 | |a Congdon, Richard T. |e Verfasser |0 (DE-588)1171532997 |4 aut | |
| 700 | 1 | |a Du Toit, Mathilda |e Verfasser |4 aut | |
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Record in the Search Index
| _version_ | 1804179060024147968 |
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| adam_text | Contents
1 Conceptual and Statistical Background for Two-Level
Models......................................................................................8
1.1 The general two-level model........................................................8
1.1.1 Level-1 model...................................................................9
1.1.2 Level-2 model...................................................................9
1.2 Parameter estimation..............................................................10
1.3 Empirical Bayes ( EB ) estimates of randomly varying level-1 coefficients, Pqj .. 10
1.4 Generalized least squares (GLS) estimates of the level-2 coefficients, yqs.......11
1.5 Maximum likelihood estimates of variance and covariance components................11
1.6 Some other useful statistics......................................................11
1.7 Hypothesis testing................................................................12
1.8 Restricted versus full maximum likelihood.................................12
1.9 Generalized Estimating Equations..................................................13
2 Working with HLM2.......................................................................15
2.1 Constructing the MDM file from raw data...........................................15
2.2 Executing analyses based on the MDM file..........................................15
2.3 Model checking based on the residual file.........................................16
2.4 Windows, interactive, and batch execution.........................................17
2.5 An example using HLM2 in Window mode..............................................17
2.5.1 Constructing the MDM file from raw data........................................17
2.5.2 Executing analyses based on the MDM file.......................................26
2.5.3 Annotated HLM2 output..........................................................31
2.5.4 Model checking based on the residual file......................................35
2.6 Handling of missing data..........................................................43
2.7 The Basic Model Specifications - HLM2 dialog box..................................45
2.8 Other analytic options............................................................46
2.8.1 Controlling the iterative procedure...........................................46
2.8.2 Estimation control.............................................................47
2.8.3 Constraints on the fixed effects............................................48
2.8.4 To put constraints on fixed effects............................................48
2.8.5 Modeling heterogeneity of level-1 variances....................................49
2.8.6 Specifying level-1 deletion variables..........................................52
2.8.7 Using design weights...........................................................52
2.8.8 Hypothesis testing.............................................................54
2.9 Output options....................................................................59
2.10 Models without a level-1 intercept................................................60
2.11 Coefficients having a random effect with no corresponding fixed effect..........60
2.12 Exploratory analysis of potential level-2 predictors..............................61
1
3 Conceptual and Statistical Background for Three-Level
Models...............................................................................63
3.1 The general three-level model................................................63
3.1.1 Level-1 model..............................................................63
3.1.2 Level-2 model..............................................................64
3.1.3 Level-3 model..............................................................65
3.1 Parameter estimation.........................................................66
3.2 Hypothesis testing q-j
4 Working with HLM3..................................................................68
4.1 An example using HLM3 in Windows mode........................................68
4.1.1 Constructing the MDM file from raw data....................................68
4.2 Executing analyses based on the MDM file.....................................73
4.2.1 An annotated example of HLM3 output........................................74
4.3 Model checking based on the residual files...................................79
4.4 Specification of a conditional model.........................................82
4.5 Other program features.......................................................87
4.5.1 Basic specifications.......................................................87
4.5.2 Iteration control..........................................................87
4.5.3 Estimation settings........................................................88
4.5.4 Hypothesis testing.........................................................88
4.5.5 Output settings............................................................88
5 Conceptual and Statistical Background for Four-Level
Models..................................................................................89
5.1 The general four-level model...................................................89
5.1.1 Level-1 model..............................................................89
5.1.2 Level-2 model..............................................................90
5.1.3 Level-3 model..............................................................90
5 1.4 Level-4 model..............................................................91
5.2 Parameter estimation...........................................................91
5.3 Hypothesis testing.............................................................92
6 Working with HLM4..................................................................93
6.1 An example using HLM4 in Windows mode........................................93
6.1.1 Constructing the MDM file from raw data....................................94
6.2 Executing analyses based on the MDM file.....................................97
6.2.1 A 4-level measurement model example........................................98
6.3 An annotated example of HLM4 output..........................................99
6.4 Other program features......................................................103
7 Conceptual and Statistical Background for Hierarchical
Generalized Linear Models (HGLM).......................................................104
7.1 The two-level HLM as a special case of HGLM..................................105
7.1.1 Level-1 sampling model....................................................105
7.1.2 Level-1 link function.....................................................105
7.1.3 Level-1 structural model..................................................106
7.2 Two-, three-, and four- level models for binary outcomes.....................106
7.2.1 Level-1 sampling model....................................................106
7.2.2 Level-1 link function.....................................................107
7.2.3 Level-1 structural model..................................................107
2
7.2.4 Level-2 and Level-3 and Level-4 models..........................................107
7.3 The model for count data........................................................107
7.3.1 Level-1 sampling model..........................................................108
7.3.2 Level-1 link function...........................................................108
7.3.3 Level-1 structural model........................................................108
7.3.4 Level-2 model...................................................................109
7.4 The model for multinomial data..................................................109
7.4.1 Level-1 sampling model..........................................................109
7.4.2 Level-1 link function...........................................................110
7.4.3 Level-1 structural model........................................................110
7.4.4 Level-2 model...................................................................110
7.5 The model for ordinal data......................................................111
7.5.1 Level-1 sampling model..........................................................111
7.5.2 Level-1 structural model........................................................111
7.6 Parameter estimation............................................................112
7.6.1 Estimation via PQL..............................................................112
7.6.2 Properties of the estimators....................................................116
7.6.3 Parameter estimation: A high-order Laplace and adaptive Gaussian Quadrature approximation
of maximum likelihood................................................................117
7.7 Unit-specific and population-average models.....................................118
7.8 Over-dispersion and under-dispersion............................................120
7.9 Restricted versus full PQL versus full ML.......................................120
7.10 Hypothesis testing..............................................................120
8 Fitting HGLMs (Nonlinear Models)......................................................121
8.1 Executing nonlinear analyses based on the MDM file...........................121
8.2 Case 1: a Bernoulli model.......................................................123
8.3 Case 2: a binomial model (number of trials, my 1)...........................130
8.4 Case 3: Poisson model with equal exposure.......................................132
8.5 Case 4: Poisson model with variable exposure....................................134
8.6 Case 5: Multinomial model.......................................................135
8.7 Case 6: Ordinal model...........................................................140
8.8 Additional features.............................................................144
8.8.1 Over-dispersion.................................................................144
8.8.2 Adaptive Gauss-Hermite Quadrature and Laplace approximations for binary models.144
8.8.3 Printing variance-covariance matrices for fixed effects...............146
8.9 Fitting HGLMs with three and four levels........................................146
9 Conceptual and Statistical Background for Hierarchical
Multivariate Linear Models (HMLM)........................................................147
9.1 Unrestricted model..............................................................148
9.1.1 Level-1 model...................................................................148
9.1.2 Level-2 model...................................................................149
9.1.3 Combined model..................................................................149
9.2 HLM with homogenous level-1 variance............................................150
9.2.1 Level-1 model...................................................................150
9.2.2 Level-2 model...................................................................150
9.2.3 Combined model..................................................................151
9.2 HLM with varying level-1 variance...............................................151
9.3 HLM with a log-linear model for the level-1 variance............................151
9.4 First-order auto-regressive model for the level-1 residuals.....................152
9.5 HMLM2: A multilevel, multivariate model.........................................152
9.5.1 Level-1 model...................................................................152
9.5.2 The combined model..............................................................153
3
9.5.3 Level-3 model...........................................................153
9.5.4 Level-2 model...........................................................153
10 Working with HMLM/HMLM2........................................................155
10.1 An analysis using HMLM via Windows mode....................................155
10.1.1 Constructing the MDM from raw data......................................155
10.2 Executing analyses based on the MDM file...................................157
10.3 An annotated example of HMLM................................................158
10.4 An analysis using HMLM2 via Windows mode....................................171
10.5 Executing analyses based on the MDM file....................................171
10.5.1 Specifications for this HMLM2 run......................................172
11 Special Features................................................................179
11.1 Latent variable analysis....................................................179
11.1.1 A latent variable analysis using HMLM. Example 1........................179
11.1.2 A latent variable analysis using HMLM: Example 2........................182
11.2 Applying HLM to multiply-imputed data.......................................185
11.2.1 Data with multiply-imputed values for the outcome or one covariate......185
11.2.2 Calculations performed..................................................186
11.2.3 Working with plausible values in HLM....................................188
11.2.4 Data with multiply-imputed values for the outcome and covariates........189
11.3 V-Known models for HLM2...................................................189
11.3.1 Data input format.......................................................190
11.3.2 Creating the MDM file...................................................190
11.3.3 Estimating a V-known model..............................................191
11.3.4 V-known analyses where Q = 1............................................194
11.3 Spatial dependence models for HLM2..........................................194
11.3.5 A spatial analysis using HLM2...........................................194
11.3.6 Other outcome variables.................................................200
12 Conceptual and Statistical Background for Cross-classified
Random Effect Models (HCM2)..........................................................201
12.1 The general cross-classified random effects models.........................201
12.1.1 Level-1 or within-cell model..........................................202
12.1.2 Level-2 or between-cell model.........................................202
12.2 Parameter estimation........................................................203
12.3 Hypothesis testing..........................................................203
13 Working with HCM2...............................................................204
13.1 An example using HCM2 in Windows mode......................................204
13.1.1 Constructing the MDM file from raw data.................................204
13.2 Executing analyses based on the MDM file....................................208
13.3 Specification of a conditional model with the effect associated with a row-specific
predictor fixed...................................................................211
13.4 Specification of a conditional model with the effect associated with the row-specific
predictor random..................................................................215
13.5 Other program features......................................................218
14 Conceptual and Statistical Background for Three-Level
Hierarchical and Cross-classified Random Effects Models
(HCM3)...............................................................................220
14.1 The general 3-level hierarchical and cross-classified random effects models ... 220
4
14.1.1 Level-1 or within-cell model..............................................221
14.1.2 Level-2 or between-cell model.............................................221
14.1.3 Level-3 model...............................................................222
14.2 Parameter estimation............................................................223
14.3 Hypothesis testing..............................................................223
15 Working with HCM3.....................................................................224
15.1 An example using HCM3 in Windows mode...........................................224
15.1.1 Constructing the MDM file from raw data.....................................224
15.1.2 Statistical package Input...................................................224
15.2 Executing analyses based on the MDM file........................................228
15.3 Other program features..........................................................233
16 Conceptual and Statistical Background for Hierarchical
Linear Model with Cross-Classified Random Effects (HLMHCM)234
16.1 The general hierarchical linear model with cross-classified random effects....234
16.1.1 Level-1 or within-unit model..............................................234
16.1.2 Level-2 or between-unit or within-cell model............................235
16.1.3 Level-3 model or between-cell model.......................................235
16.2 Parameter estimation............................................................236
16.3 Hypothesis testing..............................................................236
17 Working with HLMHCM...................................................................237
17.1 An example using HLMHCM in Windows mode.........................................237
17.1.1 Constructing the MDM file from raw data.....................................237
17.1.2 Statistical package input...................................................237
17.2 Executing analyses based on the MDM file........................................242
17.3 Specification of a level-2 and level-3 conditional model, with the effect associated
with a column-specific predictor fixed.................................................246
17.4 Other program features..........................................................251
18 Graphing Data and Models..............................................................252
18.1 Data - based graphs - two level analyses........................................252
18.1.1 Box-and-whisker plots.......................................................252
18.1.2 Scatter plots...............................................................258
18.1.3 Line plots - two-level analyses.............................................262
18.2 Model-based graphs - two level..................................................265
18.2.1 Model graphs................................................................265
18.2.2 Level-1 equation modeling...................................................271
18.2.3 Level-1 residual box-and-whisker plots......................................274
18.2.4 Level-1 residual vs predicted value.........................................276
18.2.5 Level-1 EB/OLS coefficient confidence intervals.............................278
18.2.6 Graphing categorical predictors.............................................280
18.3 Three-level applications........................................................281
A Using HLM2 in interactive and batch mode...............................................285
A.1 Using HLM2 in interactive mode....................................................285
A. 1.1 Example: constructing an MDM file for the HS B data using SPSS file input....285
A. 1.2 Example: constructing an MDM file for the HS B data using ASCII file input....286
A.2 Rules for format statements.......................................................287
A.2.1 Example: Executing an analysis using HSB.MDM..................................288
A.3 Using HLM in batch and/or interactive mode........................................291
A.4 Using HLM2 in batch mode..........................................................292
5
A.5 Printing of variance and covariance matrices for fixed effects and level-2 variances®
A. 6 Preliminary exploratory analysis with HLM2.................................297
B Using HLM3 in Interactive and Batch Mode.........................................301
B. 1 Using HLM3 in interactive mode.............................................301
B.1.1 Example; constructing an MDM file for the public school data using SPSS file input.301
B.1.2 Example: constructing an MDM file for the HS B data using ASCII file input.........302
B.1.3 Example: Executing an analysis using EG.MDM........................................303
B.2 Using HLM3 in batch mode....................................................306
B.2.1 Table of keywords and options...........................................307
B. 3 Printing of variance and covariance matrices...............................308
C Using HLM4 in Batch Mode.........................................................309
C. 1 Example: Creating an MDM file from raw data...........................................309
C. 2 Example: Creating an HLM file and running the model...................................311
D Using HGLM in Interactive and Batch Mode.........................................314
D. 1 Example: Executing an analysis using THAIUGRP.MDM..........................314
E Using HMLM in Interactive and Batch Mode.........................................320
E. 1 Constructing an MDM file...................................................320
E. 2 Executing analyses based on MDM files......................................320
E.2.1 Table of keywords and options...........................................322
E.2.2 Table of HMLM2 keywords and options.....................................322
F Using Special Features in Interactive and Batch Mode.............................324
F. 1 Example: Latent variable analysis using the National Youth Study data sets.324
F.2 A latent variable analysis to run regression with missing data..............325
F. 3 Commands to apply HLM to multiply-imputed data.............................327
F.4 Commands to apply HLM2 to create a Spatial model...............................327
G Using HCM2 in Interactive and Batch Mode.........................................328
G. 1 Using HCM2 in interactive mode.............................................328
G.1.1 Example: constructing an MDM file for the educational attainment data using SPSS file input... 328
G.1.2 Example: Executing an unconditional model analysis using ATTAIN.MDM.....329
G.1.3 Example: Executing a conditional model analysis using ATTAIN.MDM........331
G. 2 Using HCM2 in batch mode...................................................334
H Using HCM3 in Batch Mode.........................................................336
H. 1 Example: Creating an HCM3 MDM file from raw data......................................336
H. 2 Example: Creating an HCM3 HLM file and running the model..............................337
I Using HLMHCM in Batch Mode.......................................................341
I. 1 Example: Creating an HLMHCM MDM file from raw data....................................341
1.2 Example: Creating an HLMHCM HLM file and running the model.............................342
J Overview of options available by module..........................................344
References.........................................................................348
6
Subject Index
352
7
|
| any_adam_object | 1 |
| author | Raudenbush, Stephen 1946- Bryk, Anthony S. Cheong, Yuk Fai Congdon, Richard T. Du Toit, Mathilda |
| author_GND | (DE-588)117147069X (DE-588)1160786186 (DE-588)1171532997 |
| author_facet | Raudenbush, Stephen 1946- Bryk, Anthony S. Cheong, Yuk Fai Congdon, Richard T. Du Toit, Mathilda |
| author_role | aut aut aut aut aut |
| author_sort | Raudenbush, Stephen 1946- |
| author_variant | s r sr a s b as asb y f c yf yfc r t c rt rtc t m d tm tmd |
| building | Verbundindex |
| bvnumber | BV045283900 |
| classification_rvk | MR 2100 |
| ctrlnum | (OCoLC)1005261087 (DE-599)GBV883965585 |
| discipline | Soziologie |
| format | Book |
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| id | DE-604.BV045283900 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T08:13:51Z |
| institution | BVB |
| isbn | 9780894980572 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030671378 |
| oclc_num | 1005261087 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG |
| owner_facet | DE-473 DE-BY-UBG |
| physical | 351 Seiten Illustrationen, Diagramme |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | SSI, Scientific Software International |
| record_format | marc |
| spelling | Raudenbush, Stephen 1946- Verfasser (DE-588)117147069X aut HLM7 hierarchical linear and nonlinear modeling Stephen W. Raudenbush (University of Chicago), Anthony S. Bryk (The Carnegie Foundation), Yuk Fai Cheong (Emory University), Richard T. Congdon, Jr. (Harvard University), Mathilda du Toit (Scientific Software International, Inc.) HLM 7 HLM seven Seven HLM Skokie, IL SSI, Scientific Software International [2011] 351 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Programm (DE-588)4047394-6 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Hierarchische Struktur (DE-588)4465281-1 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 s Hierarchische Struktur (DE-588)4465281-1 s Programm (DE-588)4047394-6 s DE-604 Bryk, Anthony S. Verfasser (DE-588)1160786186 aut Cheong, Yuk Fai Verfasser aut Congdon, Richard T. Verfasser (DE-588)1171532997 aut Du Toit, Mathilda Verfasser aut Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030671378&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Raudenbush, Stephen 1946- Bryk, Anthony S. Cheong, Yuk Fai Congdon, Richard T. Du Toit, Mathilda HLM7 hierarchical linear and nonlinear modeling Programm (DE-588)4047394-6 gnd Multivariate Analyse (DE-588)4040708-1 gnd Hierarchische Struktur (DE-588)4465281-1 gnd |
| subject_GND | (DE-588)4047394-6 (DE-588)4040708-1 (DE-588)4465281-1 |
| title | HLM7 hierarchical linear and nonlinear modeling |
| title_alt | HLM 7 HLM seven Seven HLM |
| title_auth | HLM7 hierarchical linear and nonlinear modeling |
| title_exact_search | HLM7 hierarchical linear and nonlinear modeling |
| title_full | HLM7 hierarchical linear and nonlinear modeling Stephen W. Raudenbush (University of Chicago), Anthony S. Bryk (The Carnegie Foundation), Yuk Fai Cheong (Emory University), Richard T. Congdon, Jr. (Harvard University), Mathilda du Toit (Scientific Software International, Inc.) |
| title_fullStr | HLM7 hierarchical linear and nonlinear modeling Stephen W. Raudenbush (University of Chicago), Anthony S. Bryk (The Carnegie Foundation), Yuk Fai Cheong (Emory University), Richard T. Congdon, Jr. (Harvard University), Mathilda du Toit (Scientific Software International, Inc.) |
| title_full_unstemmed | HLM7 hierarchical linear and nonlinear modeling Stephen W. Raudenbush (University of Chicago), Anthony S. Bryk (The Carnegie Foundation), Yuk Fai Cheong (Emory University), Richard T. Congdon, Jr. (Harvard University), Mathilda du Toit (Scientific Software International, Inc.) |
| title_short | HLM7 |
| title_sort | hlm7 hierarchical linear and nonlinear modeling |
| title_sub | hierarchical linear and nonlinear modeling |
| topic | Programm (DE-588)4047394-6 gnd Multivariate Analyse (DE-588)4040708-1 gnd Hierarchische Struktur (DE-588)4465281-1 gnd |
| topic_facet | Programm Multivariate Analyse Hierarchische Struktur |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030671378&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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