成長模型

成長模型是一動態模型,可針對追蹤資料分析隨時間變化之趨勢,在管理的應用上日益普及。成長模型可利用階層線性模型 (HLM) 或結構方程模型 (SEM) 從事分析,本課程將具體說明 HLM 和 SEM的分析方法以及所對應之SAS PROC MIXED和CALIS的操作方式,也對HLM法與SEM法作優劣比較。本課程也提供成長模型在管理上的實證研究範例並進行討論。本課程之目的在於進一步強化同學的研究能力。

統計方法與資料分析,多變量分析,線性結構模式

無備註

全程由教師講授,以板書為主,並提供SAS程式給同學參考使用。

1. 學期作業: 學期作業:學期作業一次,另須繳交期末報告(自訂題目, 自行蒐集資料並進行分析)。 2. 考試狀況: 期中考。 3. 評量方法: 作業 20%,期中考 30%,期末報告 50%。

• Growth modeling

  1. Introduction to growth modeling 2. Unconditional growth modeling 3. Conditional growth modeling 4. Growth modeling by using HLM 5. Growth modeling by using SEM 6. Comparison between the HLM approach and the SEM approach 7. The use of PROC CALIS and PROC MIXED 8. Identifying plausible level-1 error covariance structures 9. Piecewise latent growth models 10. Growth modeling for latent constructs

  講授：

  36

• Applications of growth modeling

  Empirical studies in management by using growth modeling

  講授：

  9

教材以期刊論文為主。 References: [1] Bollen, K. A., & Curran, P. J. (2006). Latent curve models: A structural equation perspective. Hoboken, NJ: Wiley. [2] Chan, D. (1998). The conceptualization and analysis of change over time: An integrative approach incorporating longitudinal mean and covariance structures analysis (LMACS) and multiple indicator latent growth modeling (MLGM). Organizational Research Methods, 1, 421-483. [3] Ding, C. G., Hung, W. C., Lee, M. C., & Wang, H. J. (2017). Exploring paper characteristics that facilitate the knowledge flow from science to technology. Journal of Informetrics, 11, 244-256. [4] Ding, C. G., & Jane, T. D. (2012). Using SAS PROC CALIS to fit level-1 error covariance structures of latent growth models. Behavior Research Methods, 44, 765-787. [5] Ding, C. G., Jane, T. D., Wu, C. H., Lin, H. R., & Shen, C. K. (2017). A systematic approach for identifying level-1 error covariance structures in latent growth modelling. International Journal of Behavioral Development, 41, 444-455. [6] Ding, C. G., Lin, H. R., Wu, C. H., & Jane, T. D. (2015). Using LGM analysis to identify hidden contributors to risk in the operation of a nuclear power plant. Safety Science, 75, 64-71. [7] Ding, C. G., Wu, C. H., and Chang, P. L. (2013). The influence of government intervention on the trajectory of bank performance during the global financial crisis: A comparative study among Asian economies. Journal of Financial Stability, 9, 556-564. [8] Duncan, T. E., Duncan, S. C., & Strycker, L. A. (2006). An Introduction to latent variable growth curve modeling: Concepts, issues, and applications (2nd ed.). Mahwah, NJ: Lawrence Erlbaum. [9] Flora, D.B. (2008). Specifying piecewise latent trajectory models for longitudinal data. Structural Equation Modeling, 15, 513-533. [10] Hancock, G. R., Kuo, W. L., & Lawrence, F. R. (2001). An illustration of second-order latent growth models. Structural Equation Modeling, 8, 470-489. [11] Hung, W. C., Ding, C. G., Wang, H. J., Lee, M. C., & Lin, C. P. (2015). Evaluating and comparing the university performance in knowledge utilization for patented inventions. Scientometrics, 102, 1269-1286. [12] Kim, M., Kwok, O. M., Yoon, M., Willson, V., & Lai, M. H. C. (2016). Specification search for identifying the correct mean trajectory in polynomial latent growth models. Journal of Experimental Education, 84, 307-329. [13] Kwok, O. M., West, S. G., & Green, S. B. (2007). The impact of misspecifying the within- subject covariance structure in multiwave longitudinal multilevel models: A Monte Carlo study. Multivaraite Behavioral Research, 42, 557-592. [14] Leite, W. L. (2007). A comparison of latent growth models for constructs measured by multiple items. Structural Equation Modeling, 14, 581-610. [15] Miller, J. W., Fugate, B. S., & Golicic, S. L. (2017). How organizations respond to information disclosure: Testing alternative longitudinal performance trajectories. Academy of Management Journal, 60, 1016-1042. [16] Murphy, D. L., & Pituch, K. A. (2009). The Performance of multilevel growth curve models under an autoregressive moving average process. Journal of Experimental Education, 77, 255-282. [17] Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models (2nd ed.), London: Sage. [18] Singer, J. D. (1998). Using SAS PROC MIXED to fit multilevel models, hierarchical models, and individual growth models. Journal of Educational and Behavioral Statistics, 23, 323-355. [19] Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York: Oxford University Press. [20] Thoresen, C. J., Bradley, J. C., Bliese, P. D., & Thoresen, J. D. (2004). The big five personality traits and individual job performance growth trajectories in maintenance and transitional job stages. Journal of Applied Psychology, 89, 835-853. [21] Vandenberghe, C., Landry, G., Bentein, K., Anseel. F., Mignonac, K., & Roussel, P. (2019). A dynamic model of the effects of feedback-seeking behavior and organizational commitment on newcomer turnover. Journal of Management, published online. [22] Wu, C. H., Ding, C. G., Jane, T. D., Lin, H. R., & Wu, C. Y. (2015). Lessons from the global financial crisis for the semiconductor industry. Technological Forecasting and Social Change, 99, 47-53. [23] Wu, C. H., Ding, C. G., & Wu, C. Y. (2018). On the assessment of the performance in earnings management for the banking industry: The case of China’s banks, Applied Economics Letters, 25, 1463-1465.

地點

教授研究室

時間

週一 14:00 ~ 16:00 (可以e-mail另約其他時間)

聯絡方式

cding@mail.nctu.edu.tw