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課程名稱 |
結構方程模型
Structural Equation Models |
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開課學期 |
103-1 |
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授課對象 |
共同教育中心 統計碩士學位學程 |
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授課教師 |
翁儷禎 |
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課號 |
Psy7163 |
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課程識別碼 |
227 M8000 |
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班次 |
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學分 |
3 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期二5,6,7(12:20~15:10) |
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上課地點 |
南館地下B |
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備註 |
總人數上限：20人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1031Psy7163_ |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
... |
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課程目標 |
Course Objectives
1. To understand the principles and theories of structural equation modeling
2. To apply structural equation modeling method to simulated and real data
3. To be familiar with selected SEM software programs
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課程要求 |
待補 |
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預期每週課後學習時數 |
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Office Hours |
另約時間 備註： Office Hours: By appointments at S303. |
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指定閱讀 |
Selected Books on SEM
* Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.
Bollen, K. A., & Long, J. S. (Eds.). (1993). Testing structural equation models. Newbury Park, CA: Sage.
Hancock, G. R., & Mueller, R. O. (2013). Structural equation modeling: A second course (2nd ed.). Charlotte, Conn: IAP – Information Age Publishing.
# Kaplan, D. (2008). Structural equation modeling: Foundations and extensions (2nd ed.). Thousand Oaks, CA: Sage.
* Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: Guilford. (Ch13: How to fool yourself with SEM)
Loehlin, J. C. (2004). Latent variable models: An introduction to factor, path, and structural equation analysis (4th ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
* Long, J. S. (1983). Covariance structure model: An introduction to LISREL. Beverly Hills, CA: Sage.
# Raykov, T., & Marcoulides, G.A. (2006). A first course in structural equation modeling (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
# Schumacker, R. E., & Lomax, R. G. (2010). A beginner’s guide to structural equation modeling (3rd ed.). New York: Routledge.
Selected Articles (Please see CEIBA for more references.)
Hershberger, S. L. (2003). The growth of structural equation modeling: 1994-2001. Structural Equation Modeling, 10, 35-46.
Steiger, J. H. (2001). Driving fast in reverse: The relationship between software development, theory, and education in structural equation modeling. Journal of the American Statistical Association, 96, 331-338.
Mueller, R. O. (1997). Structural equation modeling: Back to basics. Structural Equation Modeling, 4, 353-369.
Cliff, N. (1983). Some cautions concerning the application of causal modeling methods. Multivariate Behavioral Research, 18, 115-126.
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參考書目 |
Suggested Categories of Readings
(A) Introductory journal papers
(B) Journal: Structural Equation Modeling (1994-), etc.
(C) Sage series: Long
(D) Beginner’s books: Schumacker & Lomax, Loehlin, Kline, Raykov &
Marcoulides
(E) Advanced technical books: Bollen (1989), Bollen & Long (1993), Kaplan
(2008)
(F) Software: Bentler (EQS), Joreskog & Sorbom (LISREL), Arbuckle (AMOS),
Muthen & Muthen (Mplus), SAS (CALIS), Byrne (books on software applications)
(G) Applications of SEM: Journal articles
Selected Introductory Papers
Jackson, D. L., Gillaspy, J. A., Jr., & Purc-Stephenson, R. (2009).
Reporting practices in confirmatory factor analysis: An overview and some
recommendations. Psychological Methods, 14, 6-23.
Weston, R., Gore, Jr., P. A., Chan, F., & Catalano, D. (2008). An
introduction to using structural equation models in rehabilitation
psychology. Rehabilitation Psychology, 53, 340–356.
Lei, P-W, & Wu Q. (2007). Introduction to Structural Equation Modeling:
Issues and practical considerations. Educational Measurement: Issues and
Practice, 26, 33-43.
Personality and Individual Differences (2007, 42) – a special issue
dedicated to model fit assessment in structural equation modeling
Kim, K. H., & Bentler, P. M. (2006). Data modeling: Structural Equation
Modeling. In J. Green, G. Camilli,, & P. B. Elmore, (Eds.), Handbook of
complementary methods in education research (pp. 161-175). Mahwah, NJ:
Lawrence Erlbaum Associates.
Shah, R. & Goldstein, S. M. (2006). Use of structural equation modeling in
operations management research: Looking back and forward. Journal of
Operations Management, 24, 148-169.
Schreiber, J. B., Stage, F. K., King, J., Nora, A., & Barlow, E. A. (2006).
Reporting Structural Equation Modeling and Confirmatory Factor Analysis
results: A review. Journal of Educational Research, 99, 323-337.
Ullman, J. B. (2006). Structural Equation Modeling: Reviewing the Basics and
Moving Forward. Journal of Personality Assessment, 87, 35-50.
Weston, R. & Gore, Jr. (2006). A Brief Guide to Structural Equation
Modeling. Counseling Psychologist, 34, 719-751.
Martens, M. P. (2005a). The use of Structural Equation Modeling in
counseling psychology research. Counseling Psychologist, 33, 269-298.
Martens, M. P. (2005b). Future directions of Structural Equation Modeling in
counseling psychology. Counseling Psychologist, 33, 375-382.
Stapleton, L. M., & Walter, L. L. (2005). A review of syllabi for a sample
of structural equation modeling courses. Structural Equation Modeling, 12,
642-664. [List of suggested readings provided.]
Hershberger, S. L. (2003). The growth of structural equation modeling:
1994-2001. Structural Equation Modeling, 10, 35-46.
Ullman, J. B., & Bentler, P. M. (2003). Structural equation modeling. In J.
A. Schinka & W. F. Velicer (Eds.), Handbook of psychology: Research methods
in psychology, (Vol. 2, pp. 607-634). Hoboken, NJ, US: John Wiley & Sons,
Inc.
Wolfle, L. M. (2003). The introduction of path analysis to the social
sciences, and some emergent themes: An annotated bibliography. Structural
Equation Modeling, 10, 1-34.
Bollen, K. A. (2002). Latent variables in psychology and the social
sciences. Annual Review of Psychology, 53, 605-634.
McDonald, R. P. & Ho, M.-H. R. (2002). Principles and practice in reporting
structural equation analyses. Psychological Methods, 7, 64-82.
Holbert, R. L., & Stephenson, M. T. (2002). Structural equation modeling in
the communication sciences, 1995-2000. Human Communication Research, 28,
531-551.
Russell, D. W. (2002). In search of underlying dimensions: The use (and
abuse) of factor analysis in Personality and Social Psychology Bulletin.
Personality and Social Psychology Bulletin, 28, 1629-1646.
Steiger, J. H. (2001). Driving fast in reverse: The relationship between
software development, theory, and education in structural equation modeling.
Journal of the American Statistical Association, 96, 331-338.
Boomsma, A. (2000). Reporting analyses of covariance structures.
Structural Equation Modeling, 7, 461-483.
MacCallum, R. C. & Austin, J. T. (2000). Applications of structural
equation modeling in psychological research. Annual Review of Psychology,
51, 201-226. (See references on p.204 for other reviews of SEM
applications.)
Olsson, U. H., Foss, T., Troye, S. V., & Howell, R. D. (2000). The
performance of ML, GLD, and WLS estimation in structural equation modeling
under conditions of misspecification and nonnormality. Structural Equation
Modeling, 7, 557-595. [Excellent discussion on 3 domains: Reality,
Theoretical, and Empirical.]
Mueller, R. O. (1997) Structural equation modeling: Back to basics.
Structural Equation Modeling, 4, 353-369.
Crowley. S. L. & Fan, X. (1997). Structural equation modeling: Basic
concepts and applications in personality assessment research. Journal of
Personality Assessment, 68, 508-531.
Bentler, P. M. & Dudgeon, P. (1996). Covariance structure analysis:
Statistical practice, theory, and directions. Annual Review of Psychology,
47, 563-592.
Austin, J. T. & Calderon, R. F. (1996). Theoretical and technical
contributions to structural equation modeling: An updated annotated
bibliography. Structural Equation Modeling, 3, 105-175.
Tremblay, P. F. & Gardner, R. C. (1996). On the growth of structural
equation modeling in psychological journals. Structural Equation Modeling,
3, 93-104.
Hyole, R. H., & Panter, A. T. (1995). Writing about structural equation
models. In R. H. Hoyle, (Ed.), Structural equation modeling: Concepts,
issues, and applications (pp. 158-176). Thousand Oaks, CA: Sage.
Wothke, W. (1993). Nonpositive definite matrices in structural modeling. In
K. A. Bollen & J. S. Long, (Eds.), Testing structural equation models (pp.
256-293). Newburay Park, CA: Sage. [Procedures for dealing with nonpositive
matrices in SEM]
Raykov, T., Tomer, A., & Nesselroade, J. R. (1991). Reporting structural
equation modeling results in Psychology and Aging: Some proposed guidelines.
Psychology and Aging, 6, 499-503.
Breckler, S. J. (1990). Applications of covariance structure modeling in
psychology: Cause for concern? Psychological Bulletin, 107, 260-273.
Anderson, J. C. & Gerbing, D. W. (1988). Structural equation modeling in
practice: A review and recommended two-step approach. Psychological
Bulletin, 103, 411-423.
Bentler, P. M. & Chou, C.-P. (1987). Practical issues in structural
modeling. Sociological Methods & Research, 16, 78-117.
Bentler, P. M. (1980). Multivariate analysis with latent variables: Causal
modeling. Annual Review of Psychology, 31, 419-456.
Selected Critiques
Tomarken, A. J., & Waller, N. G. (2005). Structural Equation Modeling:
Strengths, limitations, and misconceptions. Annual Review of Clinical
Psychology, 1, 31-65.
Brannick, M. T. (1995). Critical comments on applying covariance structure
modeling. Journal of Organizational Behavior, 16, 201-213.
Kelloway, E. K. (1995). Structural equation modelling in perspective.
Journal of Organizational Behavior, 16, 215-224.
Williams, L. J. (1995). Covariance structure modeling in organizational
research: Problems with the method versus applications of the method.
Journal of Organizational Behavior, 16, 225-233.
Freedman, D. A. (1991). Statistical models and show leather. Sociological
Methodology, 21, 291-313.
Berk, R. A. (1991). Toward a methodology for mere mortals. Sociological
Methodology, 21, 315-324.
Blalock, H. M. (1991). Are there really any constructive alternatives to
causal modeling? Sociological Methodology, 21, 325-335.
Mason, W. M. (1991). Freedman is right as far as he goes, but there is
more, and it’s worse: Statisticians could help. Sociological Methodology,
21, 337-351.
Freedman, D. A. (1991). A rejoinder to Berk, Blalock, and Mason.
Sociological Methodology, 21, 353-358.
Cliff, N. (1983). Some cautions concerning the application of causal
modeling methods. Multivariate Behavioral Research, 18, 115-126.
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評量方式
(僅供參考) |
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No. |
項目 |
百分比 |
說明 |
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1. |
HW |
35% |
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2. |
Introductory paper |
10% |
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3. |
Example |
10% |
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4. |
Application |
15% |
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5. |
Final |
30% |
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週次 |
日期 |
單元主題 |
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第1週 |
9/16 |
Introduction |
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第2週 |
9/23 |
From Correlation to SEM: MR, PA, CFA |
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第3週 |
9/30 |
Data Preparation |
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第4週 |
10/07 |
From Diagram, Notation, & Equations to Matrix
SEM Basics / JKW and B-W Models
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第5週 |
10/14 |
Specification: Models & Software |
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第6週 |
10/21 |
Identification |
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第7週 |
10/28 |
Estimation & Statistical Theory |
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第8週 |
11/04 |
Evaluation of Models (Bring outputs to class) |
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第9週 |
11/11 |
Fit Index / Model Modification / |
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第10週 |
11/18 |
Reporting SEM / Cautions in using SEM |
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第11週 |
11/25 |
Multi-Sample SEM
Mean Structure & Latent Growth Curve Model
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第12週 |
12/02 |
Presentation 1: Introductory papers on SEM |
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第13週 |
12/09 |
Presentation 1: Introductory papers on SEM |
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第14週 |
12/16 |
Multi-level SEM / Interaction & mediation effect |
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第15週 |
12/23 |
Presentation 2: Examples (reanalysis) |
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第16週 |
12/30 |
Presentation 3: Applications |
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第17週 |
1/06 |
Presentation 3: Applications |
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第18週 |
1/13 |
Final exam |
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