Fig. 1. Longitudinal data characteristics
Fig. 2. longitudinal trajectory of ‘lr_wage’ variable
Fig. 3. Unconditional model of LGM in SPSS AMOS
Fig. 4. 4-fractile 2-sequences association (sequential pattern) rules
Fig. 5. 4-fractile 3-sequences association (sequential pattern) rules
Fig. 6. 4-fractile 4-sequences association (sequential pattern) rules
Fig. 7. 4-fractile 5-sequences and 6-sequences association (sequential pattern) rules
Fig. 8. 5-fractile 2-sequences association (sequential pattern) rules
Fig. 9. 5-fractile 3-sequences association (sequential pattern) rules
Fig. 10. 5-fractile 4-sequences association (sequential pattern) rules
Fig. 12. Conditional Model of LGM
Table 1. Model fitness of simple linear growth trajectory
Table 2. Model fitness of derived sequential patterns vs simple linear pattern
Table 3.Rresult of initial status and slope
Table 4. Model fitness of Conditional Model
참고문헌
- Hankyoreh (2018.1.22.) http://www.hani.co.kr/arti/international/america/828794.html
- E. J. Lee & C. H. Cho. (2013). A Longitudinal Study on the Effects of Franchise's Factors and Performance -Disclosure Agreement, Korean J. of Business Administration, 26(8), 2185-2209.
- E. J. Lee & C. H. Cho. (2014). A Longitudinal Study on the Service Quality in Korean Service Industry: Focusing on KS-SQI, Journal of Korea Service Management Society, 15(2), 23-47. DOI : https://doi.org/10.15706/jksms.2014.15.2.002
- H. J. Lim & J. S. Cho. (2012). The Effect of Ownership Concentration on Firm Performance : Static and Dynamic Panel Data Analysis, Korean J. of Business Administration, 25(8), 3265-3291.
- J. H. Kim. (2018). A longitudinal study of the relationships between commitment type HRM, work team autonomy and innovation performance. The Korean Journal of Human Resource Development Quarterly, 20(2), 1-24. DOI : https://doi.org/10.18211/kjhrdq.2018.20.2.001
- Y. B. Cho, S. K. Lee & K. H. Ro. (2015). A Methodology for Analyzing the Longitudinal Data using SOM Technique, Korean J. of Business Administration, 28(1), 93-102.
- J. S. Lee & S. Y. Kim. (2017). An Exploration of Nonlinear Latent Growth Model Using Exponential Function: As an Alternative to Quadratic LGM, J. of Educational Evaluation, 30(4), 791-816.
- K. S. Kim. (2009). AMOS and LISREL, Han Academy.
- Y. B. Cho. (2018). A Data Based Methodology for Estimating the Unconditional Model of the Latent Growth Modeling, J. Digital Convergence, 16(6), 85-93. https://doi.org/10.14400/JDC.2018.16.6.085
- S. W. Menard. (2002). Longitudinal research (2nd. ed.). London: Sage Publications Inc.
- Toon Taris. (1999). A Primer in Longitudinal Data Analysis, SAGE Publications Inc. DOI : http://dx.doi.org/10.4135/9781849208512.n1
- S. S. Yeo & S. H. Park. (2012). An Appliation of Latent Growth Modeling: Use of Curriculum-Based Measurement as longitudinal Data. Asian J. of Education, 13(4), 247-273. DOI :https://doi.org/10.15753/aje.2012.13.4.011
- K. L. McArdle & D. B. Epstein. (1987). Latent Growth curves within development structural equation models. Child Development, 58, 110-133. DOI : https://doi.org/10.2307/1130295
- B. M. Byrne. (2016). Structural Equation Modeling With AMOS Basic Concepts, Applications, and Programming, Third Edition. New York; Routledge, DOI : https://doi.org/10.4324/9781315757421
- R. B. Kline. (2004). Principles and practice of structural equation modeling. New York: Guilford.
- K. A. Bollen & P. J. Curran. (2006). Latent curve models: a structural equation perspective. Hoboken, NJ: Wiley-Interscience.
- Annie Britton, Yoav Ben-Shlomo, Michaela Benzeval, Diana Kuh & Steven Bell. (2015). Life course trajectories of alcohol consumption in the United Kingdom using longitudinal data from nine cohort studies. BMC Medicine, 13(1), 47. DOI : https://doi.org/10.1186/s12916-015-0273-z
- James A. Cranford, Patrick E. Shrout, Masumi Iida, Eshkol Rafaeli, Tiffany Yip & Niall Bolger. (2006). A Procedure for Evaluating Sensitivity to Within-Person Change: Can Mood Measures in Diary Studies Detect Change Reliably? Personality and Social Psychology Bulletin, 32(7), 917-929. DOI :https://doi.org/10.1177/0146167206287721
- R Agrawal, T. Imielinski & A. Swami. (1993). Mining association rules between sets of items in large databases, Proceedings of the ACM SIGMOD Conference on Management of Data, 207-216. DOI : https://doi.org/10.1145/170036.170072
- B. W. Jin, Y. S. Cho & K. H. Ryu. (2010). Personalized e-Commerce Recommendation System using RFM method and Association Rules. J. of the Korea Society of Computer and Information, 15(12), 227-235. DOI : https://doi.org/10.9708/jksci.2010.15.12.227
- J. C. Kim, H. I Jung, H. Yoo & K. Y. Chung. (2018). Sequence Mining based Manufacturing Process using Decision Model in Cognitive Factory. Journal of the Korea Convergence Society, 9(3), 53-59. https://doi.org/10.15207/JKCS.2018.9.3.053
- Y. J. Shin & M. S. Yim. (2012). A Study of the Relationship Analysis between Mobile Application by Using An Association Rules. Journal of the Korea Convergence Society, 3(2), 19-25. https://doi.org/10.15207/JKCS.2012.3.2.019
- C. G Park & K. E Lee. (2014). A linearity test statistic in a simple linear regression. Journal of the Korean Data and Information Science Society, 25(2), 305-315. DOI : 10.7465/jkdi.2014.25.2.305