Multilevel models : (Record no. 25632)

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
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Location Shelving location Date of Cataloging Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Non-fiction CUTN Central Library CUTN Central Library Generalia 21/08/2018   005.55 WAN 33869 21/08/2018 21/08/2018 General Books

Powered by Koha