MARC details
000 -LEADER |
fixed length control field |
04082cam a2200361 a 4500 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
CUTN |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20180821101821.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
111005s2012 gw a b 001 0 eng |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783110267594 (acidfree paper) |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783110267709 (eISBN) |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783110267594 |
042 ## - AUTHENTICATION CODE |
Authentication code |
pcc |
066 ## - CHARACTER SETS PRESENT |
Alternate G0 or G1 character set |
$1 |
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
005.55 |
Edition number |
23 |
Item number |
WAN |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Wang, Jichuan. |
245 10 - TITLE STATEMENT |
Title |
Multilevel models : |
Remainder of title |
applications using SAS / |
Statement of responsibility, etc |
Jichuan Wang, Haiyi Xie, James H. Fischer. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication, distribution, etc |
Berlin ; |
-- |
Boston : |
Name of publisher, distributor, etc |
De Gruyter ; |
Place of publication, distribution, etc |
[Beijing?] : |
Name of publisher, distributor, etc |
Higher Education Press, |
Date of publication, distribution, etc |
c2012. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
ix, 264 p. : |
Other physical details |
ill. ; |
Dimensions |
25 cm. |
500 ## - GENERAL NOTE |
General note |
Interest in multilevel statistical models for social science and public health studies has been aroused dramatically since the mid-1980s. New multilevel modeling techniques are giving researchers tools for analyzing data that have a hierarchical or clustered structure. Multilevel models are now applied to a wide range of studies in sociology, population studies, education studies, psychology, economics, epidemiology, and public health.<br/><br/>This book covers a broad range of topics about multilevel modeling. The goal of the authors is to help students and researchers who are interested in analysis of multilevel data to understand the basic concepts, theoretical frameworks and application methods of multilevel modeling. The book is written in non-mathematical terms, focusing on the methods and application of various multilevel models, using the internationally widely used statistical software, the Statistics Analysis System (SAS (R)). Examples are drawn from analysis of real-world research data. The authors focus on twolevel models in this book because it is most frequently encountered situation in real research. These models can be readily expanded to models with three or more levels when applicable. A wide range of linear and non-linear multilevel models are introduced and demonstrated. |
505 ## - FORMATTED CONTENTS NOTE |
Contents |
Preface; 1 Introduction; 1.1 Conceptual framework of multilevel modeling; 1.2 Hierarchically structured data; 1.3 Variables in multilevel data; 1.4 Analytical problems with multilevel data; 1.5 Advantages and limitations of multilevel modeling; 1.6 Computer software for multilevel modeling; 2 Basics of Linear Multilevel Models; 2.1 Intraclass correlation coefficient (ICC); 2.2 Formulation of two-level multilevel models; 2.3 Model assumptions; 2.4 Fixed and random regression coefficients; 2.5 Cross-level interactions; 2.6 Measurement centering; 2.7 Model estimation; 2.8 Model fit, hypothesis testing, and model comparisons2.8.1 Model fit2.8.2 Hypothesis testing2.8.3 Model comparisons; 2.9 Explained level-1 and level-2 variances; 2.10 Steps for building multilevel models; 2.11 Higher-level multilevel models; 3 Application of Two-level Linear Multilevel Models; 3.1 Data; 3.2 Empty model; 3.3 Predicting between-group variation; 3.4 Predicting within-group variation; 3.5 Testing random level-1 slopes; 3.6 Across-level interactions; 3.7 Other issues in model development; 4 Application of Multilevel Modeling to Longitudinal Data; 4.1 Features of longitudinal data; 4.2 Limitations of traditional approaches for modeling longitudinal data; 4.3 Advantages of multilevel modeling for longitudinal data; 4.4 Formulation of growth models; 4.5 Data description and manipulation; 4.6 Linear growth models4.6.1 The shape of average outcome change over time; 4.6.2 Random intercept grow. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Social sciences |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Multilevel models (Statistics) |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Xie, Haiyi. |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Fischer, James H. |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Koha item type |
General Books |
240 10 - UNIFORM TITLE |
Uniform title |
<a href="Duo ceng tong ji fen xi mo xing">Duo ceng tong ji fen xi mo xing</a> |
240 10 - UNIFORM TITLE |
Linkage |
880-01 |
504 ## - BIBLIOGRAPHY, ETC. NOTE |
Bibliography, etc |
Includes bibliographical references (p. [247]-257) and index. |
630 00 - SUBJECT ADDED ENTRY--UNIFORM TITLE |
Uniform title |
SAS (Computer file) |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
General subdivision |
Research |
-- |
Mathematical models. |
880 10 - ALTERNATE GRAPHIC REPRESENTATION |
Linkage |
240-01/$1 |
a |
多层统计分析模型 |
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
a |
7 |
b |
cbc |
c |
orignew |
d |
1 |
e |
ecip |
f |
20 |
g |
y-gencatlg |