Introducing multilevel modeling:
Gespeichert in:
Hauptverfasser: | , |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
London [u.a.]
Sage
1998
|
Ausgabe: | 1. publ. |
Schriftenreihe: | ISM : introducing statistical methods
|
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis Klappentext |
Beschreibung: | Hier auch später erschienene, unveränderte Nachdrucke |
Beschreibung: | X, 149 Seiten Diagramme |
ISBN: | 9780761951407 9780761951414 |
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Datensatz im Suchindex
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adam_text |
CONTENTS
Preface ix
1 INTRODUCTION 1
1.1 Introduction 1
1.1.1 Hierarchies, micro and macro levels 1
1.1.2 Multilevel models 2
1.2 Examples 3
î ,2. î Income of workers in industry 3
1.2.2 Drug prevention research 4
1.2.3 School effectiveness research 4
1.2.4 Clinical therapy 5
1.2.5 Growth curve analysis 6
1.2.6 Geographical information systems 7
1.2.7 Meta-analysis 7
1.2.8 Twin and family studies 7
1.3 Summarizing discussion and definitions 8
1.3.1 Contextual models 8
1.3.2 Intra-class correlation 9
1.3.3 Fixed versus random coefficients 10
1.3.4 Cross-level interactions 12
1.3.5 Prediction 13
1.3.6 Shrinkage estimation and borrowing strength 14
1.4 Brief history 15
1.4.1 Variance components 15
1.4.2 Random coefficients 15
1.4.3 Variable coefficients 16
1.4.4 Changing coefficients 16
1.4.5 Panel data 16
1.4.6 Growth curves and repeated measurements 16
1.4.7 Bayesian linear models and empirical Bayes estimation 17
1.4.8 Moderator variables 17
1.4.9 Slopes as outcomes 17
1.5 Further reading 18
1.6 Software 18
1.6.1 HLM 19
1.6.2 VARCL 19
1.6.3 BMDP5-V 20
VI
CONTENTS
1.6.4 MLn 20
1.6*5 PROC MIXED 20
1,6*6 MIXOR and MIXREG 20
1.7 Summary 21
Note 21
2 OVERVIEW OF CONTEXTUAL MODELS 22
2.1 Introduction 22
2.2 Models 22
2.3 Data 23
2.4 Decomposition of variation 25
2.5 Total or pooled regression 26
2.6 Aggregate regression 27
2.7 The contextual model 28
2.8 The Cronbach model 29
2.9 Analysis of covariance 30
2.10 MLn analysis of contextual models 32
2.11 Summary 34
Notes 34
3 VARYING AND RANDOM COEFFICIENT MODELS 35
3.1 Introduction 35
3.2 Separate regressions 35
3.3 Varying coefficients or 'slopes as outcomes' 36
3.4 The random coefficient model 39
3.5 Assumptions of linear models 44
3.6 'Slopes-as-outcomes' analysis 45
3.7 Random coefficient results 47
3.7.1 Adding a macro-level explanatory variable 48
3.7.2 Posterior means 51
3.8 ANCOVA as alternative 53
3.9 The number of parameters 54
3.10 Summary 55
Notes 56
CONTENTS vii
4 ANALYSES 57
Introduction 57
4 J . 1 Data description 58
4. ] .2 The organization of the four sessions 61
4.2 Session 1 63
4.2.1 Notation for models 63
4.2.2 The null model 63
4.2.3 'HomeWork' and 'MathAchievement' 65
4.2.4 Random slope for 'HomeWork' 66
4.2.5 Adding 'ParentEducation' 69
4.2.6 Traditional regression analysis 70
4.3 Session 2 71
4.3.1 Introduction 71
4.3.2 A model with 'SchoolSize' 73
4.3.3 Changing 'SchoolSize' to 'Public' 74
4.3.4 Adding a cross-level interaction with 'Public' 75
4.3.5 Analyses with NELS-88 79
4.3.6 Deleting 'HomePublic' and adding 'White' using the small
data set again 80
4.3.7 Adding a random part for 'White' 82
4.3.8 Making the coefficient of 'White' fixed and adding 'MeanSES' 84
4.3.9 Deleting the school characteristic 'Public' 85
4.3.10 Adding an interaction between 'HomeWork' and 'MeanSES' 87
4.3.11 Adding another student-level variable 88
4.3.12 Analyses with NELS-88 89
4.4 Session 3 90
4.4.1 'SES' as a student-level explanatory variable 90
4.4.2 Adding a random slope 91
4.4.3 Adding 'PercentMinorities' 93
4.4.4 Adding 'MeanSES' 94
4.4.5 Analyses with NELS-88, models 2 and 3 96
4.5 Session 4 98
4.5.1 Analysis with class size and a cross-level interaction 98
4.5.2 Interaction between 'Ratio' and 'HomeWork' 99
4.5.3 Repeating the modeling session with NELS-88 101
4.6 Discussion 102
Notes 103
5 FREQUENTLY ASKED QUESTIONS 105
5.1 Introduction 105
5.2 The effects of centering 106
5.2.1 Centering in fixed effects regression models 106
5.2.2 Centering in multilevel models 107
CONTENTS
viii
5.2.3 Grand mean centering 108
5.2.4 Group mean centering 109
5.2.5 An example 110
5.2.6 Cross-level interactions with 'Public' and 'SES' 112
5.3 Modeled variance 115
5.3.1 Random intercept models 116
5.3.2 Using the null model as a way to calculate R2 117
5.3.3 Using total between variance 118
5.3.4 Conclusions 119
5.4 Power 119
5.4.1 Some simple cases 121
5.4.2 Review of simulation studies 124
5.4.3 Conclusions 126
5.5 To be or not to be random 126
5.5.1 ANCOVA versus RANCOVA versus simple regression 127
5.5.2 Fixed versus random slopes 129
5.6 Estimation techniques and algorithms 130
5.6.1 Which is best, FIML or REMl? 133
5.6.2 The effect of estimation methods on the fixed coefficients 133
5.6.3 Estimation methods for variance components 134
5.6.4 Conclusions 135
5.7 Multicollineariiy 135
Notes 137
Appendix Coding of NELS-88 Data 139
References 142
Index 147
PREFACE
This book is for researchers and students in the social sciences with no strong
background in statistics and linear algebra. However, we do assume that
traditional linear models, such as regression and analysis of variance, are
well understood.
The multilevel model presented here is a random coefficient model, with
fixed variables and random coefficients. The first chapters introduce the
model and its notation, and illustrate it with many examples. Chapter 4
starts with real examples taken from the National Education Longitudinal
Study of 1988 (see Appendix). A copy of this data set has been made available
on the Internet at ftp://ftp.stat.ucla.edu/pub/faculty/deleeuw/sagebook. The
program used for the analyses is MLn, a multilevel program for Windows®
written by researchers at the Institute of Education, University of London.
In the practical data analysis part of this book the formulas and the notation
are replaced by commands used in MLn for fitting different models. The
commands in boxes, illustrating the changes in models, are easier to read
than formulas, quicker to understand, and do not need an effort on the
reader’s part to memorize symbols and subscripts, which are always idiosyn-
crasies of authors. The book is very practical, especially for people planning to
use MLn, but is by no means restricted to such users only.
This book is different from others in further respects. It is written with prac-
titioners in mind. Many examples illustrate the possibilities of the models,
while explaining the most important features of the output. In the practical
part of the book we elaborate on problems and idiosyncrasies of this type
of modeling. We do advocate random coefficient models with caution and
reservations. Where applicable, we emphasize the trade-offs between using
this new model and more traditional models. The contents of this book and
the discussion of alternative ways of dealing with hierarchically nested data
are based on our own experience in teaching these models, on our experience
with analyses of many data sets, and on problems and questions of practi-
tioners in the field discussed in the mailing list for multilevel modeling. (In
order to subscribe to this mailing list, send an e-mail with ‘join multilevel
your name’ in the message body to mailbase@mailbase.ac.uk.)
We thank Mahtash Esfandiary (UCLA) and Rien van der Leeden (Univer-
sity of Leiden, The Netherlands) for reading parts of this book. Their com-
ments have greatly improved its readability.
iiii
the
and statistics are kept to a
rg Multilevel Modeling will
students and researchers who
multilevel models appropriately and |
any_adam_object | 1 |
author | Kreft, Ita Leeuw, Jan de 1945- |
author_GND | (DE-588)138174644 |
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dewey-raw | 300/.72 |
dewey-search | 300/.72 |
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dewey-tens | 300 - Social sciences |
discipline | Soziologie Psychologie |
edition | 1. publ. |
format | Book |
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genre | (DE-588)4151278-9 Einführung gnd-content |
genre_facet | Einführung |
id | DE-604.BV012166523 |
illustrated | Not Illustrated |
indexdate | 2024-12-06T09:03:23Z |
institution | BVB |
isbn | 9780761951407 9780761951414 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-008241988 |
oclc_num | 39681370 |
open_access_boolean | |
owner | DE-29 DE-19 DE-BY-UBM DE-739 DE-20 DE-11 DE-706 DE-703 DE-384 |
owner_facet | DE-29 DE-19 DE-BY-UBM DE-739 DE-20 DE-11 DE-706 DE-703 DE-384 |
physical | X, 149 Seiten Diagramme |
publishDate | 1998 |
publishDateSearch | 1998 |
publishDateSort | 1998 |
publisher | Sage |
record_format | marc |
series2 | ISM : introducing statistical methods |
spelling | Kreft, Ita Verfasser aut Introducing multilevel modeling Ita Kreft, Jan de Leeuw 1. publ. London [u.a.] Sage 1998 X, 149 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier ISM : introducing statistical methods Hier auch später erschienene, unveränderte Nachdrucke Kontextanalyse swd Multiniveau-analyse gtt Sciences sociales - Modèles mathématiques Sciences sociales - Modèles mathématiques ram Sciences sociales - Méthodes statistiques Sciences sociales - Recherche - Modèles mathématiques Sociologie - Modèles mathématiques ram Sociologie - Recherche - Modèles mathématiques Mathematisches Modell Sozialwissenschaften Soziologie Social sciences Research Mathematical models Sociology Research Mathematical models Sozialwissenschaften (DE-588)4055916-6 gnd rswk-swf Multi-level-Verfahren (DE-588)4344428-3 gnd rswk-swf Empirische Sozialforschung (DE-588)4014606-6 gnd rswk-swf Multiple Regression (DE-588)4170720-5 gnd rswk-swf Statistisches Modell (DE-588)4121722-6 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf (DE-588)4151278-9 Einführung gnd-content Empirische Sozialforschung (DE-588)4014606-6 s DE-604 Multi-level-Verfahren (DE-588)4344428-3 s Multiple Regression (DE-588)4170720-5 s Mathematisches Modell (DE-588)4114528-8 s 1\p DE-604 Sozialwissenschaften (DE-588)4055916-6 s Statistik (DE-588)4056995-0 s 2\p DE-604 Statistisches Modell (DE-588)4121722-6 s 3\p DE-604 Leeuw, Jan de 1945- Verfasser (DE-588)138174644 aut Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008241988&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008241988&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
spellingShingle | Kreft, Ita Leeuw, Jan de 1945- Introducing multilevel modeling Kontextanalyse swd Multiniveau-analyse gtt Sciences sociales - Modèles mathématiques Sciences sociales - Modèles mathématiques ram Sciences sociales - Méthodes statistiques Sciences sociales - Recherche - Modèles mathématiques Sociologie - Modèles mathématiques ram Sociologie - Recherche - Modèles mathématiques Mathematisches Modell Sozialwissenschaften Soziologie Social sciences Research Mathematical models Sociology Research Mathematical models Sozialwissenschaften (DE-588)4055916-6 gnd Multi-level-Verfahren (DE-588)4344428-3 gnd Empirische Sozialforschung (DE-588)4014606-6 gnd Multiple Regression (DE-588)4170720-5 gnd Statistisches Modell (DE-588)4121722-6 gnd Mathematisches Modell (DE-588)4114528-8 gnd Statistik (DE-588)4056995-0 gnd |
subject_GND | (DE-588)4055916-6 (DE-588)4344428-3 (DE-588)4014606-6 (DE-588)4170720-5 (DE-588)4121722-6 (DE-588)4114528-8 (DE-588)4056995-0 (DE-588)4151278-9 |
title | Introducing multilevel modeling |
title_auth | Introducing multilevel modeling |
title_exact_search | Introducing multilevel modeling |
title_full | Introducing multilevel modeling Ita Kreft, Jan de Leeuw |
title_fullStr | Introducing multilevel modeling Ita Kreft, Jan de Leeuw |
title_full_unstemmed | Introducing multilevel modeling Ita Kreft, Jan de Leeuw |
title_short | Introducing multilevel modeling |
title_sort | introducing multilevel modeling |
topic | Kontextanalyse swd Multiniveau-analyse gtt Sciences sociales - Modèles mathématiques Sciences sociales - Modèles mathématiques ram Sciences sociales - Méthodes statistiques Sciences sociales - Recherche - Modèles mathématiques Sociologie - Modèles mathématiques ram Sociologie - Recherche - Modèles mathématiques Mathematisches Modell Sozialwissenschaften Soziologie Social sciences Research Mathematical models Sociology Research Mathematical models Sozialwissenschaften (DE-588)4055916-6 gnd Multi-level-Verfahren (DE-588)4344428-3 gnd Empirische Sozialforschung (DE-588)4014606-6 gnd Multiple Regression (DE-588)4170720-5 gnd Statistisches Modell (DE-588)4121722-6 gnd Mathematisches Modell (DE-588)4114528-8 gnd Statistik (DE-588)4056995-0 gnd |
topic_facet | Kontextanalyse Multiniveau-analyse Sciences sociales - Modèles mathématiques Sciences sociales - Méthodes statistiques Sciences sociales - Recherche - Modèles mathématiques Sociologie - Modèles mathématiques Sociologie - Recherche - Modèles mathématiques Mathematisches Modell Sozialwissenschaften Soziologie Social sciences Research Mathematical models Sociology Research Mathematical models Multi-level-Verfahren Empirische Sozialforschung Multiple Regression Statistisches Modell Statistik Einführung |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008241988&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=008241988&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
work_keys_str_mv | AT kreftita introducingmultilevelmodeling AT leeuwjande introducingmultilevelmodeling |