[下载]硕士学位论文 农村居民食物消费结构变动及其对粮食需求影响的实证分析

Textbook Examples
Multilevel Analysis: An introduction to basic and advanced multilevel modeling
Tom Snijders and Roel Bosker

This is one of the books available for loan from Academic Technology Services (see Statistics Books for Loan for other such books, and details about borrowing). See Where to buy books for tips on different places you can buy these books.

You can obtain more information about the book, including access to the data files from the web site for the book.

• Data Files
  
  • HLM - mlbook1.SSM,
    
  • MLwiN - mlbook1.ws , ch12.ws
    
  • Mplus - mlbook1.dat, mlbook1-a.dat, ch14.dat
    
  • SAS - mlbook1.sas7bdat , ch12.sas7bdat
    
  • Stata - mlbook1.dta , ch12.dta
    
  • SPSS - mlbook1.sav , ch12.sav

	HLM	MLwiN	Mplus	SAS	Stata	Chapter Title
Chapter 1						Introduction
Chapter 2						Multilevel Theories, Multi-Stage Sampling, and Multilevel Models
Chapter 3						Statistical Treatment of Clustered Data
Chapter 4	Chap 4	Chap 4	Chap 4	Chap 4		The Random Intercept Model
Chapter 5		Chap 5		Chap 5		The Hierarchical Linear Model
Chapter 6		Chap 6		Chap 6		Testing and Model Specification
Chapter 7						How much does the model explain?
Chapter 8		Chap 8				Heteroschedasticity
Chapter 9						Assumptions of the Hierarchical Linear Model
Chapter 10						Designing Multilevel Studies
Chapter 11						Crossed Random Effects
Chapter 12		Chap 12				Longitudinal Data
Chapter 13						Multivariate Multilevel Models
Chapter 14			Chap 14			Discrete Dependent Variables
Chapter 15						Software

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Centre for Multilevel Modelling

Multilevel Modelling
Introduction	Centre for Multilevel Modelling
Publications and References	Software reviews
Links
MLwiN Software
About MLwiN	Downloads
Ordering	Support and workshops
Previous version 1.10
Contact us	Search MLwiN site

Multilevel Data Analysis

Don Hedeker

Multilevel Data

Reading material: Hedeker, D., Gibbons, R.D., & Flay, B.R. (1994). Random-effects regression models for clustered data with an example from smoking prevention research. Journal of Consulting and Clinical Psychology, 62, 757-765. (pdf file)

Overheads: Multilevel Analysis: An Applied Introduction (pdf file)

Example using SAS PROC MIXED:
TVSFPMIX.SAS - ASCII file with SAS code from analysis of TVSFP dataset using a few different MIXED models. Also includes individual-level and aggregate-level analyses.
TVSFP2B.DAT - ASCII datafile for example above.

---

Longitudinal Data

Reading material: Hedeker, D. (2004). An introduction to growth modeling. In D. Kaplan (Ed.), Quantitative Methodology for the Social Sciences. Thousand Oaks CA: Sage Publications. (pdf file)

Overheads: Mixed Models for Longitudinal Data: An Applied Introduction (pdf file)

Example using SAS PROC MIXED:
RIESBYM.SAS - ASCII file with SAS code from analysis of Riesby dataset using a few different MIXED models. Includes grouping variable and curvilinear effect of time.
RIESBY.DAT - ASCII datafile for example above.

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Missing Values in Longitudinal Data

Reading material: Hedeker, D., & Gibbons, R.D. (1997). Application of random-effects pattern-mixture models for missing data in longitudinal studies. Psychological Methods, 2, 64-78. (pdf file)

Overheads: Mixed Pattern-Mixture Models for Missing Data (pdf file)

Example using SAS PROC MIXED:
schizpm2.sas - ASCII file with SAS code from analysis of NIMH Schizophrenia dataset to perform a pattern-mixture analysis. Includes IML code to do the mixing over the pattern results.
SCHIZREP.DAT - ASCII datafile for example above.

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Longitudinal Dichotomous Data

Reading material: Hedeker, D. and Gibbons, R.D. "Longitudinal Data Analysis" (in progress).
Chapter 9: Mixed-effects regression models for binary outcomes. (pdf file)

Overheads: Mixed Models for Longitudinal Dichotomous Data (pdf file)

Example using SAS PROC NLMIXED:
schzbnl.sas - SAS code for mixed-effects logistic regression analysis of NIMH Schizophrenia data.
SCHIZX1.DAT - ASCII datafile for example above.

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Longitudinal Ordinal Data

Reading material: Hedeker, D. and Gibbons, R.D. "Longitudinal Data Analysis" (in progress).
Chapter 10: Mixed-effects regression models for ordinal outcomes. (pdf file)

Overheads: Mixed Models for Longitudinal Ordinal Data (pdf file)

Example using SAS PROC NLMIXED:
schzonl.sas - SAS code for mixed-effects ordinal logistic regression analysis of NIMH Schizophrenia data.

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Sample Size Estimation for Longitudinal Studies

Reading material: Hedeker, D., Gibbons, R.D., & Waternaux, C. (1999). Sample size estimation for longitudinal designs with attrition: comparing time-related contrasts between two groups. Journal of Educational and Behavioral Statistics, 24:70-93. (pdf file)

Overheads: (pdf file)

RMASS2.EXE contains:
- executable program for sample size determination based on this paper.
RMASS2.PDF contains:
- PDF version of program guide

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More information and materials:

Don's short course on Longitudinal Data Analysis

Don's 15-week course on Longitudinal Data Analysis

The MIX website

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Multilevel Analysis of Rural Outmigration in Guandong, China

Software Reviews of Multilevel Analysis Packages

Reviews Home Page
Tables
Datasets
aML	Mplus
EGRET	R
GENSTAT	SAS
GLLAMM	S-Plus
HLM	SPSS
LIMDEP	STATA
LISREL	SYSTAT
MIXREG	WINBUGS
MLwiN

Textbook Examples:Multilevel Models

Joop Hox

This is one of the books available for loan from Academic Technology Services (see Statistics Books for Loan for other such books, and details about borrowing). See Where to buy books for tips on different places you can buy these books. You can find more information about this book, including the data files, table of contents and sample chapters at the web site for the book.

• Data Files
  
  • Description of Files
    
  • HLM (Use all the SPSS files)
    
  • MLwiN data files
    
  • Mplus
    
  • SAS data files
    
  • Stata data files
    
  • SPSS data files

	HLM	MLwiN	SAS	Stata	Chapter Title
Chapter 1	NA	NA	NA	NA	Introduction to multilevel analysis
Chapter 2	Chap 2	Chap 2	Chap 2	Chap 2	The basic two-level regression model: introduction
Chapter 3	NA	NA	NA	NA	Estimation and hypothesis testing in multilevel regression
Chapter 4	Chap 4	Chap 4	Chap 4	Chap 4	Some important methodological and statistical issues
Chapter 5	Chap 5	Chap 5	Chap 5	Chap 5	Analyzing longitudinal data
Chapter 6		Chap 6			The logistic model for dichotomous data and proportions
Chapter 7		Chap 7	Chap 7		Cross-classified multilevel models
Chapter 8	Chap 8	Chap 8		Chap 8	The multilevel approach to meta-analysis
Chapter 9		Chap 9			Multivariate multilevel regression models
Chapter 10					Sample sizes and power analysis in multilevel regression
Chapter 11		Chap 11			Advanced methods for estimation and testing
Chapter 12					Multilevel factor models
Chapter 13					Multilevel path models
Chapter 14					Latent curve models

[此贴子已经被作者于2006-5-2 12:23:59编辑过]

Structural Equation Modeling and Multilevel Analysis Books

• Advanced Structural Equation Modeling: Issues and Techniques Edited by George A. Marcoulides and Randall E. Schumaker 376 pages. 1996.
  
• Basics of Structural Equation Modeling Geoffrey M. Maruyama. 328 pages. 1997.
  
• A Beginner's Guide to Structural Equation Modeling Randall E. Schumacker and Richard G. Lomax. 498 pages. 2004.
  
• Contemporary Psychometrics Edited by: Albert Maydeu-Olivares and John J. McArdle. 600 pages. 2005.
  
• A First Course in Structural Equation Modeling Tenko Raykov, George A. Marcoulides. 216 pages. 2000.
  
• Hierarchical Linear Models: Applications and Data Analysis Methods - Second Edition Stephen W. Raudenbush. 485 pages. 2002.
  
  
• HLM 6: Hierarchical Linear and Nonlinear Modeling Stephen W. Raudenbush, Anthony S. Bryk, Yuk Fai Cheong and Richard Congdon. 306 pages. 2004.
  
• Interaction and Nonlinear Effects in Structural Equation Modeling Edited by Randall E. Schumacker, George A. Marcoulides. 320 pages. 1998.
  
• Interactive LISREL User's Guide Mathilda Du Toit, Stephen Du Toit, with a contribution by Douglas Hawkins. 500 pages. 2001.
  
• Introducing Lisrel Adamantios Diamantopoulos and Judy A. Siguaw. 171 pages. 2000.
  
• Introducing Multilevel Modeling Ita G. G. Kreft, Jan de Leeuw. 160 pages. 1998.
  
  
• An Introduction to Multilevel Modeling Techniques Ronald H. Heck, Scott L. Thomas. 224 pages. 2000.
  
• Introduction to Latent Variable Growth Curve Modeling Terry E. Duncan, Susan C. Duncan, Lisa A. Strycker, Fuzhong Li, Anthony Albert. 208 pages. 1999.
  
• Latent Variable and Latent Structure Models Edited by George A. Marcoulides and Irini Moustaki. 280 Pages. 2002
  
• Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis John C. Loehlin. 317 pages. 2004.
  
• LISREL 8 New Statistical Features Karl G. Jöreskog, Dag Sörbom, Stephen Du Toit and Mathilda Du Toit. 248 pages. 2001.
  
  
• LISREL 8: Structural Equation Modeling with the SIMPLIS Command Language Karl G. Jöreskog and Dag Sörbom. 226 pages. 1996.
  
• LISREL 8 User's Reference Guide Karl G. Jöreskog and Dag Sörbom. 378 pages. 1996.
  
• Modeling Intraindividual Variability With Repeated Measures Data Edited by D. S. Moskowitz and Scott L. Hershberger. 276 Pages. 2002
  
• Modeling Longitudinal and Multilevel Data: Practical Issues, Applied Approaches, and Specific Examples Edited by Todd D. Little, Kai U. Schnabel, and Jürgen Baumert. 308 pages. 2000.
  
• Multilevel Analysis: An introduction to basic and advanced multilevel modeling (Hardcover) Tom Snijders and Roel J. Bosker. 272 pages. 1999.
  
  
• Multilevel Analysis: Techniques and Applications Joop Hox. 304 pages. 2002
  
• Multilevel Modeling: Methodological Advanced, Issues, and Applications Edited by Steven P. Reise and Naihua Duan. 314 Pages. 2003
  
• New Developments and Techniques in Structural Equation Modeling Edited by George A. Marcoulides and Randall E. Schumacker. 333 Pages. 2001
  
• PRELIS 2 User's Reference Guide Karl G. Jöreskog and Dag Sörbom. 224 pages. 1996.
  
• The Sage Handbook of Quantitative Methodology for the Social Sciences Edited by David Kaplan. 511 pages. 2004.
  
  
• Structural Equation Modeling: Concepts, Issues, and Applications Edited by Rick H. Hoyle. 290 pages. 1995.
  
• Structural Equation Modeling: Foundations and Extensions David Kaplan. 215 pages. 2000.
  
• Structural Equation Modeling: Present and Future Edited by Stephen DuToit, Robert Cudeck, and Dag Sörbom. 620 pages. 2001.
• Structural Equation Modeling with AMOS: Basic Concepts, Applications and Programming Barbara M. Byrne. 338 pages. 2001
  
• Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS: Basic Concepts, Applications, and Programming Barbara M. Byrne. 424 pages. 1998.
  
• Testing Structural Equation Models Edited by Kenneth A. Bollen, J. Scott Long. 328 pages. 1993.
  
• Using LISREL for Structural Equation Modeling: A Researcher's Guide E. Kevin Kelloway. 164 pages. 1998.

[此贴子已经被作者于2006-5-2 12:07:23编辑过]

Wolfgang Ludwig-Mayerhofer:The Multilevel Modeling Page

What is Multilevel Modeling?

Multilevel modeling (MM) is a family of statistical procedures that try to come to terms with influences that are located on different, well, levels. So naturally the question arises what is meant by "level".

One way to think about it is as follows: People do not live entirely on their own, but rather embedded in social units. Even though today, in a globalized world, we may say that people have relationships with other people all over the world, most people have some relationships that are more special than others. People who are linked together via special relationships frequently communicate among each other, and thus the possibility rises that the people you are linked to influence your views. So we may think about the individuals as one (the lowest) level and their network (whether it consists of people that are met in person or of people communication with whom may take place only via artifical media) as a next (higher) level.
(Note that " low" and " high" are just names; we may well think about things the other way round. "High" just means something like "aggregate"; that is, several individuals -- entities on the "low" level -- are seen as agglutinated).

A second way: Opportunities structure the behaviour of individuals, and as many people select their opportunities by local proximity, the region in which a person lives may enhance or restrict his or her opportunity. For instance, if a person lives in a region with high unemployment, this may influence his or her behaviour about acceptable wage levels when looking for a new job.

A third way: Often people, be it voluntarily or not, are subject to common external influences. Take, for instance, a university professor. All the students that come to her or him are subject to her or his way of teaching. Could be that this way of teaching influences these students (even though this certainly -- if sometimes fortunately -- happens less frequently than we professors might desire). Therefore, again we may think of a multitude of professors as the "higher" level units and of their many students as the "lower" level units.

For a variety of reasons, data referring to more than one level often cannot be analyzed by conventional statistical models. For instance, classical OLS regression analysis requires that residuals from individual observations are not correlated. This requirement becomes doubtful if these individual observations are subject to the same influences or are related to each other in other ways.

After so many words, this page -- at the moment -- does very little: It provides a few links to MM related pages, and it also provides selected references to the literature, with short comments.

Links

• The Centre for Multilevel Modeling at Bristol – the follow-up of the former Multilevel Models Project at London
• Software Review – a subsite of the Centre for Multilevel Modeling of tremendous help for users, therefore mentioned specifically here.
• The Multilevel Modelling Portal at the UCLA
• Note specifically this very helpful paper by Judith Singer. The paper is about how to use SAS to estimate multilevel models, and this page also demonstrates how this can be achieved with specialized (HLM or MLwiN) as well as multi-purpose (SPSS, S-Plus) software.
• Tom Snijders' Page
• Wolfgang Langer's Multilevel Page