• 授課教師: 吳裕益
    教學大綱:※※※請遵守智慧財產權觀念、不得不法影印※※※

    國立高雄師範大學 特殊教育研究所 104學年度教學綱要

    科目名稱:結構方程模式        □必修     R選修       教師:吳裕益       

    任課班級:博士班                                      助教:

    每學期開課學分數:上學期   學分    下學期 3 學分

    總學分數:  3   學分   每週上課時數:  3   小時

    連繫電話: 2314        上課地點:

    Office hours:星期三1000-1200 (研究室)

    E-Mail: t1850@nknucc.nknu.edu.tw

     

    一、課程目標

     

    ※※請遵守智慧財產權觀念、不得非法影印※※

     

    本課程目標

    核心能力指標(博士班)

     

    1.          具備特殊教育通論領域之進階專業知能

    ★★★★★

    2.          具備特殊教育特定領域之進階專業知能

    ★★★

    3.          具備研究批判與發表之能力

    ★★

    4.          具有學術倫理

    註:★表示比重10%(總計100%)

     

    二、教學目標

    1.瞭解結構方程模式之原理及在教育研究之應用(核心能力[]24

    2.實際應用結構方程模式軟體來分析研究資料及撰寫研究報告(核心能力[]24

     

    三、評量方式

    課堂討論(核心能力[]23)、作業(核心能力[]23、撰寫報告(核心能力[]24

     

    、主要讀本及參考書目

    1.主要讀本

    吳裕益(未出版):結構方程模式的理論與應用。高師大特教系。

    李茂能(2006):結構方程模式軟體Amos之簡介及其在測驗編製之應用。台北:心理。

    李茂能(2009):圖解AMOS在學術研究之應用。台北:五南。

    余民寧(2006):潛在項模式:SIMPLIS的應用。台北:高等教育。

    Arbuckle,J. L. (2007). AMOS 7.0 user’s guide. Chicago: SmallWaters.

     

    2.其他參考書目

    邱浩政(2003):結構方程模式:LISREL的理論、技術與應用。台北:雙葉。

    黃芳銘(2002):結構方程模式理論與應用。台北:五南。

    Bollen, K. A. (1989). Structural equations with latent variables. NY: Wiley.

    Byrne, B. M. (2001). Structural equation modeling with AMOS. NJ: LEA.

    Duncan, T. E., Duncan, S. C., Strycker, L. A., Li, F., and Alpert, A. (1999). An introduction to latent variable growth curve modeling: Concepts, Issues, and applications. NJ: LEA.

    Hoyle, R. H. (Ed.). (1995). Structural equation modeling: Concept, issues, and applications . CA: Sage.

    Kaplan, D. K. (2000). Structural equation modeling: Foundations and extensions. CA: Sage.

    Kline, R.B. (1998). Principle and practice of structural equation modeling. NY: Guilford.

    Little, T.D., Schnabel, K.U., and Baumert, J. (Eds.). (2000). Modeling longitudinal and multilevel data: Practical issues, applied approaches, and specific examples. NJ: LEA.

    Marcoulides, G. A., and Schumacker, R. E. (Eds.). (1996). Advanced structural equation modeling: issues and techniques. NJ: LEA.

    Marcoulides, G. A., and Schumacker, R. E. (Eds.). (2001). New developments and techniques in structural equation modeling. NJ: LEA.

    Schumacker, R.E., and Marcoulides, G. A. (Eds.). (1998). Interaction and nonlinear effects in structural equation modeling. NJ: LEA.

     

    五、教學進度

    週別

             

    1

    結構方程模式基本概念

    2

    結構方程模式基本概念

    3

    結構方程模式適合度之評鑑

    4

    結構方程模式適合度之評鑑

    5

    AMOS軟體簡介

    6

    AMOS軟體在回歸及徑路分析之應用

    7

    AMOS軟體在驗證性因素分析之應用

    8

    AMOS在多群體分析之應用

    9

    AMOS在多群體分析之應用

    10

    AMOS在共變數分析之應用

    11

    AMOS在多模式分析之應用

    12

    AMOS在縱貫資料分析之應用

    13

    AMOS在縱貫資料分析之應用

    14

    AMOS的貝氏SEM

    15

    LISREL軟體應用

    16

    LISREL軟體應用

    17

    PLS軟體應用

    18

    PLS軟體應用

     

    結構方程模式其他閱讀資料(Readings about SEM

     

    通論性SEMGeneral SEM

     

    MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51, 201-226.

    Hershberger, S. (2003). The growth of structural equation modeling: 1994-2001. Structural Equation

    Modeling, 10, 35-46.

    Williams, L. J., Edwards, J. R., & Vandenberg, R. J. (2003). Recent advances in causal modeling methods for organizational and management research. Journal of Management, 29(6), 903-936.

    Andrew J. Tomarken and Niels G.Waller (2005). Structural equation modeling: Strengths, limitations, andmisconceptions, Annual Review of Clinical Psychology, 1: 3165.

     

     

    SEM分析程序(Procedure for SEM

     

    Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and

    recommended two-step approach. Psychological Bulletin, 103, 411423.

    Hayduk, L. A., & Glaser, D. N. (2000). Jiving the Four-Step, Waltzing Around Factor Analysis, and Other Serious Fun. Structural Equation Modeling, 7(1), 135.

    Mulaik, S. A., &Millsap, R. E. (2000). Doing the Four-Step Right. Structural Equation Modeling, 7, 36-73.

    Bollen, K. A. (2000). Modeling Strategies: In Search of the Holy Grail. Structural Equation Modeling, 7, 74-81.

    Bentler, P. M. (2000). Rites,Wrongs, and Gold in Model Testing. Structural Equation Modeling, 7, 82-91.

    Herting, J. R., & Costner, H. L. (2000). Another Perspective on "The Proper Number of Factors" and the Appropriate Number of Steps. Structural Equation Modeling, 7, 92-110.

    Hayduk, L. A., & Glaser, D. N. (2000). Doing the Four-Step, Right-2-3, Wrong-2-3: A Brief Reply to

    Mulaik and Millsap; Bollen; Bentler; and Herting and Costner. Structural Equation Modeling, 7, 111-123.

     

     

    SEM發現報告撰寫(Reporting SEM findings

     

    McDonald, R. P., & Ho, M. R. (2002). Principles and practice in reporting structural equation analysis.

    Psychological Methods,7, 64-82.

    Jackson, D. L., Gillaspy, Jr., J. A., & Purc-Stephenson, R. (2009). Reporting practices in confirmatory

    factor analysis: An overview and some recommendations. Psychological Methods,14(1), 623.

    Schreiber, J. B. (2008). Core reporting practices in structural equation modeling. Administrative Pharmacy, 4, 83-97.

     

     

    模式適合度(Model fit

     

    Hu, Li-tze, & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis:

    conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 155.

    Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual

    Differences, 42, 815-824.

     

     

    樣本大小與檢定力議題(Sample size and Power issue

     

    Kim, K. H. (2005). The relation among fit indexes, power, and sample size in structural equation modeling. Structural Equation Modeling, 12(3), 368-90.

    MacCallum, R. C, & Browne, M. W., & Cai, L. (2006). Testing differences between nested covariance

    structure models: power analysis and null hypotheses. Psychological Methods, 11(1), 19-35.

     

     

    一階及高階驗證性因素分析(CFA & HCFA

     

    Jackson, D. L. (2007). The effect of the number of observations per parameter in misspecified confirmatory factor analytic models. Structural Equation Modeling, 14(1), 48-76.

    DiStefano, C. (2002). The impact of categorization with confirmatory factor analysis. Structural Equation Modeling, 9(3), 327-346.

    Koufteros, X., Babbar, S., & Kaighobadi, M. (2009). A paradigm for examining second-order factor

    models employing structural equation modeling. International Journal of Production Economics, 120, 633-652.

    Silvia, P. J. (2008). Another look at creativity and intelligence: Exploring higher-order models and probable 3 confounds. Personality and Individual Differences, 44(4), 1012-1021.

     

     

    測量不變性與題目分群(Measurement Invariance and parceling

     

    Schmitt, N., & Kuljanin, G. (2008). Measurement invariance: Review of practice and implications. Human Resource Management Review, 18(4), 210-222.

    Cheung. G. W. (2008). Testing Equivalence in the structure, means, and variances of higher-order

    constructs with structural equation modeling. Organizational Research Methods, 9(3), 369-403.

    Williams, L. J., & O'Boyle Jr, E. H. (2008).Measurement models for linking latent variables and indicators: A review of human resource management research using parcels. Human Resource Management Review, 18, 233-242.

    Meade, A. W., & Kroustalis, C. M. (2006). Problems with item parceling for confirmatory factor analytic: Tests of measurement invariance. Organizational Research Methods 9(3), 369-403.

     

     

    SEM交互作用與中介效果分析(Interaction and Medication in SEM

     

    Marsh, H. W., Wen, Z., & Hau, K. T. (2004). Structural equation models of latent interactions: Evaluation of alternative estimation strategies and indicator construction. Psychological Methods, 9, 275300.

    Little, T. D., Bovaird, J. A., & Widaman, K. F. (2006). On the merits of orthogonalizing powered and

    product terms: Implications for modeling interactions among latent variables. Structural Equation

    Modeling, 13, 497519.

    Marsh, H. W., Wen, Z., & Hau, K. T., Little, T. D., Bovaird, J. A., & Widaman, K. F. (2007).

    Unconstrained Structural Equation Models of Latent Interactions: Contrasting Residual- and

    Mean-Centered Approaches. Structural Equation Modeling , 14(4), 570580.

    Chan, W. (2007). Comparing indirect effects in SEM: A sequential model fitting method using

    covariance-equivalent sepcifications. Structural Equation Modeling , 14(2), 326-346.

     

     

    多層次SEMMultilevel Structural Equation Modeling

     

    Lüdtke, O., Marsh, H. W., Robitzsch, A., Trautwein, U., Asparouhov, T., & Muthén, B. (2008). The

    Multilevel Latent Covariate Model: A New, More Reliable Approach to Group-Level Effects in

    Contextual Studies. Psychological Methods, 13(3), 203229.

    Zyphur, M. J., Kaplan, S. A., & Christian, M. S. (2008). Assumptions of Cross-Level Measurement and

    Structural Invariance in the Analysis of Multilevel Data: Problems and Solutions. Group Dynamics: Theory, Research, and Practice, 12(2), 127-140.

     

     

    混合模式(Mixture Modeling

     

    Steinley. D., & McDonald, R. P. (2007). Examining factor score distributions to determine the nature of latent spaces. Multivariate Behavioral Research, 42(1), 133-156.

    Lubke, G. H. & Muthén, B. (2005). Investigating population heterogeneity with factor mixture models.

    Psychological Methods, 10, 21-39.

    Bauer, D. J., & Curran, P. J. (2004). The integration of continuous and discrete latent variable models:

    Potential problems and promising opportun