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http://dx.doi.org/10.7465/jkdi.2014.25.4.847

The study of changes in performance in KLPGA using growth curve analysis  

Kim, Nam Jin (Department of Physical Education, Korea University)
Min, Dae Kee (Department of Information & Statistics, Duksung Women's University)
Publication Information
Journal of the Korean Data and Information Science Society / v.25, no.4, 2014 , pp. 847-855 More about this Journal
Abstract
In recent years, women's monetary rewards in golf increased and their performances have improved significantly compared to other sports. Sports marketing has become more active in Asia and the number of Korean players in LPGA with good scores are increasing. For these reasons, golf is becoming increasingly popular. The prize money is higher than in other sports and the economic benefits are increasing due to the financial incentives such as sponsorships. Many of these prospects actively affect women's golf. Certain rookies continue to increase and their performances improve day by day. In this study, I analyze the changes in performance over time of last 5 years from 2009 using growth curve analysis. According to the results of analysis, driving distance and average putting skills developed but green in regulation decreased.
Keywords
Fixed effect; growth curve model; longitudinal data; mixed model; random effect;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 Min, D. K. (2011). The study for effectiveness of golf skills to adjust average score using path analysis in 2010 PGA. Journal of the Korean Data & Information Science Society, 22, 65-71.   과학기술학회마을
2 Mirman, D., Dixon, J. A. and Magnuson, J. S. (2008). Statistical and computational models of visual world paradigm: Growth curves and individual difference. Journal of Memory and Language, 59, 475-494.   DOI   ScienceOn
3 Littell, R. C., Milliken, G. A., Stroup, W. W. and Wolfinger, R. D. (2006). SAS system for mixed models, SAS Institute Inc., N.C.
4 Panik, J. M. (2013). Growth curve modeling theory and application, Wiley, New York.
5 Singer, J. D. and Willett, J. B. (2003). Applied longitudinal data analysis : Modeling change and event occurrence, Oxford University Press, New York.
6 Twisk, J. W. R. (2013). Applied longitudinal data analysis for epidemiology, Cambridge University Press, Cambridge.
7 Jo, J. A. and Chang, J. U. (2013). A statistical analysis of the fat mass repeated measures data using mixed model. Journal of the Korean Data & Information Science Society, 24, 303-310.   과학기술학회마을   DOI   ScienceOn
8 Kim, H. S., Lee, W. J. and Lee, M. S. (2012). Effectiveness of golf skills to average score in PGA. Journal of the Korean Data & Information Science Society, 23, 505-514.   과학기술학회마을   DOI   ScienceOn
9 Littell, R. C., Henry, P. R. and Ammerman, C. B. (1998). Statistical analysis of repeated measures data using SAS procedure. Journal of Animal Science, 76, 1216-1231.   DOI
10 Strathe, A. B., Danfaer, A., Sorensen, H. and Kebreab, E. (2010). A multilevel nonlinear mixed-effects approach to model growth in pigs. Journal of Animal Science, 88, 638-649   DOI   ScienceOn