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Social Media Marketing Research 社會媒體行銷研究 1 1002SMMR09 TMIXM1A Thu 7,8 (14:10-16:00) L511 Confirmatory Factor Analysis Min-Yuh Day 戴敏育 Assistant Professor.

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Presentation on theme: "Social Media Marketing Research 社會媒體行銷研究 1 1002SMMR09 TMIXM1A Thu 7,8 (14:10-16:00) L511 Confirmatory Factor Analysis Min-Yuh Day 戴敏育 Assistant Professor."— Presentation transcript:

1 Social Media Marketing Research 社會媒體行銷研究 1 1002SMMR09 TMIXM1A Thu 7,8 (14:10-16:00) L511 Confirmatory Factor Analysis Min-Yuh Day 戴敏育 Assistant Professor 專任助理教授 Dept. of Information Management, Tamkang University Dept. of Information ManagementTamkang University 淡江大學 淡江大學 資訊管理學系 資訊管理學系 http://mail. tku.edu.tw/myday/ 2012-05-10

2 週次 日期 內容( Subject/Topics ) 1 101/02/16 Course Orientation of Social Media Marketing Research 2 101/02/23 Social Media: Facebook, Youtube, Blog, Microblog 3 101/03/01 Social Media Marketing 4 101/03/08 Marketing Research 5 101/03/15 Marketing Theories 6 101/03/22 Measuring the Construct 7 101/03/29 Measurement and Scaling 8 101/04/05 教學行政觀摩日 (--No Class--) 9 101/04/12 Paper Reading and Discussion 課程大綱 ( Syllabus) 2

3 週次 日期 內容( Subject/Topics ) 10 101/04/19 Midterm Presentation 11 101/04/26 Exploratory Factor Analysis 12 101/05/03 Paper Reading and Discussion 13 101/05/10 Confirmatory Factor Analysis 14 101/05/17 Paper Reading and Discussion 15 101/05/24 Communicating the Research Results 16 101/05/31 Paper Reading and Discussion 17 101/06/07 Term Project Presentation 1 18 101/06/14 Term Project Presentation 2 課程大綱 ( Syllabus) 3

4 Outline Confirmatory Factor Analysis (CFA) – Structured Equation Modeling (SEM) Covariance based SEM – LISREL Partial-least-squares (PLS) based SEM – PLS 4

5 Types of Factor Analysis Exploratory Factor Analysis (EFA) – is used to discover the factor structure of a construct and examine its reliability. It is data driven. Confirmatory Factor Analysis (CFA) – is used to confirm the fit of the hypothesized factor structure to the observed (sample) data. It is theory driven. 5 Source: Hair et al. (2009), Multivariate Data Analysis, 7th Edition, Prentice Hall

6 Structural Equation Modeling (SEM) Structural Equation Modeling (SEM) techniques such as LISREL and Partial Least Squares (PLS) are second generation data analysis techniques 6 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

7 Data Analysis Techniques Second generation data analysis techniques – SEM PLS, LISREL – statistical conclusion validity First generation statistical tools – Regression models: linear regression, LOGIT, ANOVA, and MANOVA 7 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

8 The TAM Model 8 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

9 Structured Equation Modeling (SEM) Structural model – the assumed causation among a set of dependent and independent constructs Measurement model – loadings of observed items (measurements) on their expected latent variables (constructs). 9 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

10 Structured Equation Modeling (SEM) The combined analysis of the measurement and the structural model enables: – measurement errors of the observed variables to be analyzed as an integral part of the model – factor analysis to be combined in one operation with the hypotheses testing SEM – factor analysis and hypotheses are tested in the same analysis 10 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

11 Use of Structural Equation Modeling Tools 1994-1997 11 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

12 SEM models in the IT literature Partial-least-squares-based SEM – PLS Covariance-based SEM – LISREL 12 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

13 Comparative Analysis between Techniques 13 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

14 Capabilities by Research Approach 14 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

15 TAM Model and Hypothesis 15 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

16 TAM Causal Path Findings via Linear Regression Analysis 16 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

17 Factor Analysis and Reliabilities for Example Dataset 17 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

18 TAM Standardized Causal Path Findings via LISREL Analysis 18 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

19 Standardized Loadings and Reliabilities in LISREL Analysis 19 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

20 TAM Causal Path Findings via PLS Analysis 20 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

21 Loadings in PLS Analysis 21 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

22 AVE and Correlation Among Constructs in PLS Analysis 22 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

23 Generic Theoretical Network with Constructs and Measures 23 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

24 Number Of Covariance-based SEM Articles Reporting SEM Statistics in IS Research 24 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

25 Number of PLS Studies Reporting PLS Statistics in IS Research (Rows in gray should receive special attention when reporting results) 25 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

26 26 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

27 27 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

28 28 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

29 The holistic analysis that SEM is capable of performing is carried out via one of two distinct statistical techniques: 1. covariance analysis – employed in LISREL, EQS and AMOS 2. partial least squares – employed in PLS and PLS-Graph 29 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

30 Comparative Analysis Based on Statistics Provided by SEM 30 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

31 Comparative Analysis Based on Capabilities 31 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

32 Comparative Analysis Based on Capabilities 32 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

33 Heuristics for Statistical Conclusion Validity (Part 1) 33 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

34 Heuristics for Statistical Conclusion Validity (Part 2) 34 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

35 35 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

36 36 Source: Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000)

37 Gefen, David and Straub, Detmar (2005) "A Practical Guide To Factorial Validity Using PLS-Graph: Tutorial And Annotated Example," Communications of the Association for Information Systems: Vol. 16, Article 5. Available at: http://aisel.aisnet.org/cais/vol16/iss1/5 37 Source: Gefen, David and Straub, Detmar (2005)

38 PLS-Graph Model 38 Source: Gefen, David and Straub, Detmar (2005)

39 Extracting PLS-Graph Model 39 Source: Gefen, David and Straub, Detmar (2005)

40 Displaying the PLS-Graph Model 40 Source: Gefen, David and Straub, Detmar (2005)

41 PCA with a Varimax Rotation of the Same Data 41 Source: Gefen, David and Straub, Detmar (2005)

42 Correlations in the lst file as compared with the Square Root of the AVE 42 Source: Gefen, David and Straub, Detmar (2005)

43 Summary Confirmatory Factor Analysis (CFA) & Structured Equation Modeling (SEM) Covariance based SEM – LISREL Partial-least-squares (PLS) based SEM – PLS 43

44 References Joseph F. Hair, William C. Black, Barry J. Babin, Rolph E. Anderson (2009), Multivariate Data Analysis, 7th Edition, Prentice Hall Gefen, David; Straub, Detmar; and Boudreau, Marie-Claude (2000) "Structural Equation Modeling and Regression: Guidelines for Research Practice," Communications of the Association for Information Systems: Vol. 4, Article 7. Available at: http://aisel.aisnet.org/cais/vol4/iss1/7 Straub, Detmar; Boudreau, Marie-Claude; and Gefen, David (2004) "Validation Guidelines for IS Positivist Research," Communications of the Association for Information Systems: Vol. 13, Article 24. Available at: http://aisel.aisnet.org/cais/vol13/iss1/24 Gefen, David and Straub, Detmar (2005) "A Practical Guide To Factorial Validity Using PLS-Graph: Tutorial And Annotated Example," Communications of the Association for Information Systems: Vol. 16, Article 5. Available at: http://aisel.aisnet.org/cais/vol16/iss1/5 44


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