Hoyle, Rick H. (ed.) Handbook of Structural Equation Modeling. NY: Guilford Press. (HSEM)

Transcription

1 SOSC 5760 Structural Equation Modeling Spring 2015 PREREQUISITES INSTRUCTOR Sound background in graduate level of statistics Raymond S. Wong Office: Room 2373 ( ) Office Hours: 10:00-12:00 pm Wednesday and by appointment only TA: Zhonglu Li TIME/PLACE 3:00-5:50 pm Tuesday, Room 5486 (Lift 25-26) SUBJECT MATTER This course focuses on sociological (and other social-scientific) applications of path analysis and structural equation models. Following a review of basic ideas about the structure, interpretation, estimation, and inference in recursive causal models, the course will work through problems of specification and identification in latent-variable models and non-recursive models, using published examples where possible. The LISREL model will be introduced, and its use in the specification of a variety of models will be reviewed. They include: factor models, MIMIC models, recursive and non-recursive models (with and without latent variables), multiple group models (with or without latent mean structures), models of repeated measurement, models with missing data, the specification of latent structural models for ordinal data, latent growth curve modeling, and multilevel structural equation models. COURSE REQUIREMENT (1) About 6-8 weekly exercises will be assigned (50%). Grades will be based on the completion of the exercises. Answer to all assignments should be lucid, orderly, self-contained, and brief. Printed output from the analysis should also be turned in, but just handing the output will not be good enough. All work must be complete and turned in on time. (2) A self-contained research paper that utilizes the types of models introduced in the seminar (50%), that is, it should contain literature review, data, findings, and discussion sections. The paper is due at the end of the semester and the normal length is about pages (content only, not counting cover page, abstract, tables, figures, bibliography, and appendices). REQUIRED TEXTBOOKS Byrne, Barbara M Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS: Basic Concepts, Applications, and Programming. Mahwah, NJ: Lawrence Erlbaum Associates. (hereafter SEM) Hoyle, Rick H. (ed.) Handbook of Structural Equation Modeling. NY: Guilford Press. (HSEM) Jöreskog, Karl and Dag Sörbom LISREL 8: User's Reference Guide. Chicago, IL: Scientific Software International. (LISREL8) Kline, Rex Principles and Practice of Structural Equation Modeling. Third Edition. New York: Guilford. (PPSEM). All required textbooks have been reserved at the library. The LISREL 8 manual, together with the PRELIS, and SIMPLIS manuals, are all located at the computer lab. Also, you can visit the Guilford Press to download all computer files (EQS, LISREL, and MPLUS) for the examples used in the Kline s book: You can also obtain online documentation and examples of LISREL8 from the SSI website ( and the student version of the program (LISREL9.1) can be downloaded from:

2 SOSC OTHER USEFUL TEXTBOOKS Bollen, Kenneth A Structural Equations with Latent Variables. N.Y.: John Wiley. Duncan, Otis Dudley Introduction to Structural Equation Models. New York: Academic Press. Hancock, Gregory R. and Ralph O. Mueller (Eds.) Structural Equation Modeling: A Second Course. Greenwich. CT: Information Age Publishing, Inc. Kaplan, David Structural Equation Modeling: Foundations and Extensions. Second Edition. Thousand Oaks, CA: Sage Publications. Kelloway. E. Kevin Using LISREL for Structural Equation Modeling: A Researcher's Guide. Thousand Oaks, CA: Sage Publications. Loehlin, John Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis. Fourth Edition. Mahwah, NJ: Lawrence Erlbaum Associates. Long, J. Scott Confirmatory Factor Analysis: A Preface to LISREL. Beverly Hills: Sage Publications. Long, J. Scott Covariance Structure Models: An Introduction to LISREL. Beverly Hills: Sage Publications. Marcoulides, George A. and Randall E. Schumacker (eds.) Advanced Structural Equation Modeling: Issues and Techniques. Mahwah, NJ: Lawrence Erlbaum Associates. Mulaik, Stanley A Linear Causal Modeling with Structural Equations. Boca Raton, FL: Chapman & Hall/CRC. Schumacker, Randall E. and Richard G. Lomax A Beginner s Guide to Structural Equation Modeling. Third Edition. London: Routledge Academic. Schumacker, Randall E. and George A. Marcoulides (eds.) Interaction and Nonlinear Effects in Structural Equation Modeling. Mahwah, NJ: Lawrence Erlbaum Associates. All required textbooks have been reserved at the HKUST Library. All other required readings (other than textbooks) can be found in the course website: COMPUTATION An earlier windows version of LISREL (8.8) will be used. Copies of the software have already been installed in the Computer Lab. Please check with the Lab staff and/or class TA about how to use the program. As indicated above, the student version of LISREL (9.1) can be installed in your personal computer as well. Note that the student version has a few limitations: (1) Basic statistical analyses and data manipulation are restricted to a maximum of 20 variables; (2) Structural equation modeling is restricted to a maximum of 16 observed variables; (3) Multilevel modeling is restricted a maximum of 15 variables; (4) It can only import ASCII, tab-delimited and comma-delimited and SOME (NOT ALL) SPSS for Windows data files by using the Import Data option on the File menu; and (5) The Export Data option on the File menu is restricted to ASCII, tab-delimited and comma-delimited data files. However, the student version should be more than sufficient for pedagogical purposes. Depending on individual circumstances, the above limitations may or may not pose serious problems for your final paper. Finally, it is possible to use vast amount of computer time with very little progress unless great care is exercised in the preparation for maximum-likelihood estimation using LISREL. Therefore you should take extreme care in planning and preparing the specifications of the LISREL command structures before submitting the job.

3 SOSC TENTATIVE SCHEDULE AND READINGS Starred (*) items are required readings and unless indicated otherwise, they are available from class website. Week 1 (3 Feb) Review: Matrix Algebra and Multiple Regression * 1. Kline, PPSEM, Ch * 2. Matseuda, Ross L Key Advances in the History of Structural Equation Modeling. Pp in Handbook of Structural Equation Modeling, edited by Rich H. Hoyle. NY: Guilford Press. (HSEM) * 3. Mulaik, Stanley Linear Causal Modeling with Structural Equations. Chapter 2. Boca Raton, FL: Chapman & Hall. (Other useful resources from the web include: and * 4. Mels, Gerhard LISREL for Windows: Getting Started Guide. Lincolnwood, IL: Scientific Software International, Inc. * 5. Du Toit, Mathilda, and Stephen du Toit Interactive LISREL: User s Guide. Lincolnwood, IL: Scientific Software International, Inc. 6. Steiger, James H Driving Fast in Reverse: The Relationship between Software Development, Theory, and Education in Structural Equation Modeling. Journal of the American Statistical Association 96(453): Mulaik, Stanley A History of Path Analysis. Pp in Encyclopedia in Statistics in Behavioral Science, Volume 2, edited by Brian S. Everitt and David C. Howell. Chichester, UK: John Wiley & Sons. Week 2 (10 Feb) Introduction to Structural Equation Models * 1. Kline, PPSEM, Ch * 2. Byrne, SEM, Ch * 3. Mulaik, Stanley A. and Lawrence R. James Objectivity and Reasoning in Science and Structural Equation Modeling. Pp in Structural Equation Modeling: Concepts, Issues, and Applications, edited by Rick H. Hoyle. Thousand Oaks, CA: Sage Publications. * 4. Kline, Rex B Assumptions in Structural Equation Modeling. Pp in Handbook of Structural Equation Modeling, edited by Rich H. Hoyle. NY: Guilford Press. (HSEM) * 5. Ho, Moon-ho Ringo, Stephen Stark, and Olexander Chernshenko Graphical Representation of Structural Equation Models Using Path Diagrams. Pp in Handbook of Structural Equation Modeling, edited by Rich H. Hoyle. NY: Guilford Press. (HSEM) * 6. Bollen, Kenneth A. and Rich H. Hoyle Latent Variables in Structural Equation Modeling. Pp in Handbook of Structural Equation Modeling, edited by Rich H. Hoyle. NY: Guilford Press. (HSEM) 7. MacCullan, Robert C. and James T. Austin Applications of Structural Equation Modeling in Psychological Research. Annual Review of Psychology 51: Bielby, William T. and Robert M. Hauser Structural Equation Models. Annual Review of Sociology 3:

4 SOSC Week 3 (17 Feb) Recursive Models * 1. Kline, PPSEM, Ch. 5. * 2. Alwin, Duane F. and Hauser, Robert M The Decomposition of Effects in Path Analysis. American Sociological Review 40: * 3. Sobel, Michael Direct and Indirect Effects in Linear Structural Equation Models. Sociological Methods & Research 16(1): * 4. Joreskog and Sorbom, LISREL 8, Ch. 2 and 4. * 5. Du Toit, Stephen, Mathilda du Toit, Gerhard Mels, and Yan Cheng LISREL for Windows: LISREL Syntax Files. Lincolnwood, IL: Scientific Software International, Inc. * 6. Cheong, JeeWon and David P. MacKinnon Mediation/Indirect Effects in Structural Equation Modeling. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) 7. Bollen, Kenneth A Total, Direct, and Indirect Effects in Structural Equation Models. Sociological Methodology 17: Du Toit, Stephen, Mathilda du Toit, Gerhard Mels, and Yan Cheng LISREL for Windows: SIMPLIS Syntax Files. Lincolnwood, IL: Scientific Software International, Inc. Week 4 (24 Feb) Confirmatory Factor Analysis: Identification and Estimation * 1. Byrne. SEM, Ch * 2. Kline, PPSEM, Ch. 6, 7 & 9. * 3. Joreskog and Sorbom, LISREL 8, Ch. 3 and 6. * 4. Brown, Timothy A. and Michael T. Moore. Confirmatory Factor Analysis. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) * 5. Hoyle, Rick H Confirmatory Factor Analysis. Pp in Handbook of Applied Multivariate Statistics and Mathematical Modeling, edited by Howard E. A. Tinsley and Steven D. Brown. San Diego, CA: Academic Press. 6. Long, J. Scott Confirmatory Factor Analysis: A Preface to LISREL. Beverly Hills, CA: Sage Publications. Week 5 (3 Mar) Models with Unobservable Variables and MIMIC Models * 1. Kline, PPSEM, Ch. 10. * 2. Byrne, SEM, Ch. 7. * 3. Joreskog, Karl G. and Arthur S. Goldberger Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable. Journal of the American Statistical Association 70: * 4. Joreskog and Sorbom, LISREL 8, Ch Alwin, Duane F. and David J. Jackson Measurement Models for Response Errors in

5 SOSC Surveys: Issues and Applications. Pp in Karl F. Schuessler (ed.), Sociological Methodology San Francisco, CA: Jossey-Bass. 6. Bielby, William T., Robert M. Hauser, and David L. Featherman Response Errors of Blacks and Nonblack Males in Models of the Intergenerational Transmission of Socioeconomic Status. American Journal of Sociology 82: Hauser, Robert M., Shu-Ling Tsai, and William H. Sewell A Model of the Stratification Process with Response Error in Social and Psychological Variables. Sociology of Education 556: Week 6 (10 Mar) Modeling and Testing Strategies * 1. Kline, PPSEM, Ch. 8. * 2. Byrne, SEM, Ch. 11. * 3. Joreskog and Sorbom, LISREL 8, Ch. 8. * 4. West, Stephen G., Aaron B. Taylor, and Wei Wu Model Fit and Model Selection in Structural Equation Modeling. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) * 5. Chou, Chih-Ping and Jimi Huh Model Modification in Structural Equation Modeling. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) 6. Satorra, Albert and Peter M. Bentler Corrections to Test Statistics and Standard Errors in Covariance Structure Analysis. Pp in Latent Variables Analysis: Applications for Development Research, edited by Alexander von Eye and Clifford C. Clogg. Thousand Oaks, CA: Sage Publications. 7. Williams, Larry J Equivalent Models: Concepts, Problems, Alternatives. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) 8. Marsh, Herbert W., Kit-Tai Hau, and Zhonglin Wen In Search of Golden Rules: Comment on Hypothesis-Testing Approaches to Setting Cutoff Values for Fit Indexes and Dangers in Overgeneralizing Hu and Bentler s (1999) Findings. Structural Equation Modeling: A Multidisciplinary Journal 11(3): Week 7 (17 Mar) Non-Recursive Models * 1. Kline, PPSEM, Ch. 6 (Rules for Non-Recursive Models). * 2. Hauser, Robert M. and Raymond Sin-Kwok Wong Sibling Resemblance and Inter-Sibling Effects in Educational Attainment. Sociology of Education 62: * 3. Kohn, Melvin L. and Carmi Schooler Job Conditions and Personality: A Longitudinal Assessment of Their Reciprocal Effects. American Journal of Sociology 87: Week 8 (24 Mar) Multiple-Group LISREL Models * 1. Byrne, LVM, Ch * 2. Sorbom, Dag and Karl G. Joreskog The Use of LISREL in Sociological Model Building. Pp in David J. Jackson and Edgar F. Borgotta (eds.), Factor Analysis and

6 SOSC Measurement in Sociological Research: A Multidimensional Perspective. Beverly Hills, CA: Sage. * 3. Joreskog and Sorbom, LIRESL 8, Ch. 9. * 4. Green, Samuel B. and Marilyn S. Thompson A Flexible Structural Equation Modeling Approach for Analyzing Means. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) 5. Wolfe, Lee M High School Seniors' Reports of Parental Socioeconomic Status: Black-White Differences. Pp in Peter Cuttance and Russell Ecob (eds.), Structural Modeling by Example. Cambridge: Cambridge University Press. 6. Kluegel, James R., Royce Singleton, Jr. and Charles E. Starnes Subjective Class Identification: A Multiple Indicator Approach. American Sociological Review 42: Faulbaum, Frank Intergroup Comparisons of Latent Means Across Waves. Sociological Methods & Research 15(3): Week 9 (31 Mar) Week 10 (7 Apr) Multiple-Group LISREL Models (Continued) No Class (Mid-Term Break) Week 11 (14 Apr) Models with Missing Data * 1. Joreskog and Sorbom, LISREL 8, Ch. 10: * 2. Graham, John W. and Donna L. Coffman Structural Equation Modeling with Missing Data. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) * 3. Rovine, Michael J Latent Variables and Missing Data Analysis. Pp in Latent Variables Analysis: Applications for Development Research, edited by Alexander von Eye and Clifford C. Clogg. Thousand Oaks, CA: Sage Publications. * 4. Allison, Paul Estimation of Linear Models with Incomplete Data. Pp in Sociological Methodology 1987,edited by Clifford C. Clogg. Washington, D.C.: American Sociological Association. * 5. Allison, Paul D. and Robert M. Hauser Reducing Bias in Estimates of Linear Model by Remeasurement of a Random Subsample. Sociological Methods & Research 19: Lee, Sik-Yum Estimation for Structural Equation Models with Missing Data. Psychometrika 51: Enders, Craig K A Primer on Maximum Likelihood Algorithms for Use with Missing Data. Structural Equation Modeling: A Multidisciplinary Journal 8(1): Schafer, Joseph and John Graham Missing Data: Our View of the State of the Art. Psychological Methods 7(2): Davey, Adam, Jyoti Savla and Zupei Luo Issues in Evaluating Model Fit with Missing Data. Structural Equation Modeling: A Multidisciplinary Journal 12(4): Enders, Craig K Applying the Bollen-Stine Bootstrap for Goodness-of-Fit Measures to Structural Equation Models with Missing Data. Multivariate Behavioral Research 37(3):

7 SOSC Week 12 (21 Apr) Models for Ordinal Data/Interaction * 1. Joreskog and Sorbom, LISREL 8, Ch. 7. * 2. West, Stephen, John F. Finch, and Patrick J. Curran Structural Equation Models with Nonnormal Variables: Problems and Remedies. Pp in Structural Equation Modeling: Concepts, Issues, and Applications, edited by Rick H. Hoyle. Thousand Oaks, CA: Sage Publications. * 3. Mislevy, Robert J Recent Developments in the Factor Analysis of Categorical Variables. Journal of Educational Statistics 11:3-31. * 4. Bovaird, James A. and Natalie A. Koziol Measurement Models for Ordered-Categorical Indicators. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) * 5. Marsh, Herbert W., Zhonglin Wen, Benjamin Nagengast, and Kit-Tai Hau Structural Equation Models of Latent Interaction. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) * 6. Du Toit, Stephen, Mathilda du Toit, Gerhard Mels, and Yan Cheng LISREL for Windows: PRELIS User s Guide. Lincolnwood, IL: Scientific Software International, Inc. 7. Muthen, Bengt O A General Structural Equation Model with Dichotomous, Ordered Categorical and Continuous Latent Variable Indicators. Psychometrika 49: Muthen, Bengt O Dichotomous Factor Analysis of Symptom Data. Sociological Methods and Research 18: Browne, M Asymptotically Distribution-Free Methods for the Analysis of Covariance Structures. British Journal of Mathematical and Statistical Psychology 37: Week 13 (28 Apr) Latent Growth Curve Modeling * 1. Kline, PPSEM, Ch. 11. * 2. Biesanz, Jeremy C Autoregressive Longitudinal Models. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) * 3. McArdle, John J Latent Curve Modeling of Longitudinal Growth Data. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) * 4. Willet, John B. and Magaret K. Keiley Using Covariance Structure Analysis to Model Change Over Time. Pp in Handbook of Applied Multivariate Statistics and Mathematical Modeling, edited by Howard E. A. Tinsley and Steven D. Brown. San Diego, CA: Academic Press. * 5. Willet, John B. and Kristen L. Bub Structural Equation Modeling: Latent Growth Curve Analysis. Pp in Encyclopedia of Statistics in Behavioral Science, Volume 4, edited by Brian S. Everitt and David C. Howell. Chichester, UK: John Wiley & Sons. 6. Bollen, Kenneth A. and Patrick J. Curran Latent Curve Models: A Structural Equation Perspective. Hoboken, NJ: John Wiley & Sons. 7. Preacher, Kristopher J., Aaron L. Wichman, Robert C. MacCallum, and Nancy E. Briggs

8 SOSC Latent Growth Curve Modeling. Thousand Oaks, CA: Sage Publications. 8. Preacher, Kristopher J., Aaron L. Wichman, Robert C. MacCallum, and Nancy E. Briggs Latent Growth Curve Modeling. Thousand Oaks, CA: Sage Publications. Week 14 (5 May) Multilevel SEM * 1. Kline, PPSEM, Ch. 12. * 2. Steele, Fiona Structural Equation Modeling: Multilevel. Pp in Encyclopedia of Statistics in Behavioral Science, Volume 4, edited by Brian S. Everitt and David C. Howell. Chichester, UK: John Wiley & Sons. * 3. Rabe-Hesketh, Sophia, Anders Skrondal, and Xiaohui Zheng Multilevel Structural Equation Modeling. Pp in Handbook of Structural Equation Modeling, edited by Rick H. Hoyle. NY: Guilford Press. (HSEM) * 4. Hox, Joop and Reinoud D. Stoel Multilevel and SEM Approaches to Growth Curve Modeling. Pp in Encyclopedia of Statistics in Behavioral Science, volume 3, edited by Brian S. Everitt and David C. Howell. Chichester, UK: John Wiley & Sons. 5. Bauer, Daniel Estimating Multilevel Linear Models as Structural Equation Models. Journal of Behavioral Statistics 28(2): Teachman, Jay, Greg J. Duncan, W. Jean Yeung, and Dan Levy Covariance Structure Models for Fixed and Random Effects. Sociological Methods and Research 30(2):271-8

9 SOSC SEM Software Amos is part of SPSS. Calis is part of SAS. EQS is published by Multivariate Software. LISREL is published by Scientific Software. MPlus is published by Muthen and Muthen. Mx is available from Virginia Commonwealth University. OpenMx is available from the University of Virginia. RAMONA is part of Systat. sem is an open source library for R. SEPath is part of Statistica. SmartPLS is available from the University of Hamburg. Generalized SEM in Stata 13.