MEZUNİYET SÜRELERİNİ ETKİLEYEN FAKTÖRLERİN YAŞAM ÇÖZÜMLEMESİ İLE İNCELENMESİ

Yıl 2018, Cilt: 16 Sayı: 1, 649 - 664, 31.03.2018

Hatice Işık Nihal Ata Tutkun Durdu Karasoy

Öz

Öz; Sağlık bilimlerinde kullanımı
yaygın olan yaşam çözümlemesinin sosyal bilimlerdeki kullanımı son yıllarda
önem kazanmıştır.  İşletme, ekonomi,
eğitim gibi alanlarda uygulamaları görülmektedir. Eğitim alanında öğrencilerin
mezuniyet süreleri ya da belli bir konuyu kavrama süreleri gibi konularda yaşam
çözümlemesi yöntemlerinden yararlanılmaktadır. Bu çalışmada Hacettepe
Üniversitesi İstatistik Bölümü’den 1967 yılından 2015 yılına kadar mezun olan
3182 öğrencinin mezuniyet süreleri ve etkilediği düşünülen faktörler
incelenmiştir. Normal süresi içinde eğitimini tamamlamayanlar başarısız gözlem
olarak nitelendirilmiştir. Kaplan-Meier yaşam olasılıkları ve Tarone-Ware testi
sonuçları elde edilmiştir. Yarı
parametrik bir yöntem olan Cox regresyon modeli uygulanmış,  ancak modelin varsayımı olan orantılı
tehlikeler varsayımı sağlanmadığından kullanılamamıştır. Bu modele alternatif
olan hızlandırılmış başarısızlık süresi modelleri ve sonrasında da zayıflık
modeli uygulanmıştır. Veri için en uygun modelin zayıflık terimi içeren log-lojistik
hızlandırılmış başarısızlık süresi modeli olduğu görülmüştür. Bu modele göre
akademik ortalama (p-değeri=0.007), 
İngilizce hazırlık (p-değeri=0.003) ve tercih sırası (p-değeri=0.001)
değişkenleri mezuniyet sürelerini etkileyen önemli faktörler olarak belirlenmiştir.

Anahtar Kelimeler

Cox regresyon modeli, durdurma, hızlandırılmış başarısızlık süresi modelleri, mezuniyet süresi, zayıflı

Kaynakça

• AALEN, O.O. (1994), “Effects of Frailty in Survival Analysis”, Statistical, Methods in Medical Research, S:3, ss.227-243. BEAN, J.P. (1980), “Dropouts and Turnover: The synthesis and Test of a Causal Model of Student Attrition”, Research in Higher Education, S:12, ss.155–187. BENNETT, R. (2003), “Determinants of Undergraduate Student Drop Out Rates in a University Business Studies Department”, Journal of Further and Higher Education, 27(2), 123-140. BLOSSFELD, H. P. (1990), “Changes in educational careers in the Federal Republic of Germany”, Sociology of Education, 63, 165-177. BUCKLEY, P.J., ve HOOLEY, G.J. (1988), “The Non-Completion of Doctoral Research in Management: Symptoms, Causes and Cures”, Educational Research, S:30, ss.110-119. CATERALL, J. S. (1987), “On the Social Costs of Dropping Out of School”, The High School Journal, S:71, ss.19-30. CIVIAN, J. T. (1990), Using Proportional Hazard Models to Examine Time to Doctorate, (Yayınlanmamış doktora tezi), Harvard University, Cambridge, MA. COLLET, D. (2003), Modelling Life Data in Medical Research, London: Chapman&Hall. COX, D.R. (1972), “Regression models and life-tables”, Journal of the Royal Statistical Society, Series B, S:34(2), ss.187-220. DESJARDINS, S. L., AHLBURG, D., ve MCCALL, B. (1994), “Studying the Determinants of Student Stopout: Identifying "True" from Spurious Time-Varying Effects”, Paper presented at the 34th Annual Forum of the Association for Institutional Research, New Orleans, LA. FLEMING, T.R. ve HARRINGTON, D.P. (1991), Counting Processes and Survival Analysis, New York: Wiley GRAMBSCH, P.M. ve THERNEAU, T.M. (1994), “Proportional hazards tests and diagnostics based on weighted residuals”, Biometrika, S.81, ss. 515-526. GUTIERREZ, R.G. (2002), “Parametric Frailty and Shared Frailty Models”, The Stata Journal, S:2(1), ss.22–44. HOUGAARD, P. (1995), “Frailty Models for Survival Data”, Lifetime Data Analysis, S:1, ss.255–273. JOHNES, J. ve TAYLOR, J. (1989), “Undergraduate Non-Completion Rates: Differences Between UK Universities”, Higher Education, S:18, ss.209-225. KARASOY, D. ve SEZAYİ, S. (2014), “Yaşam çözümlemesinde hızlandırılmış başarısızlık süresi modelleri ve bir uygulama”, Suleyman Demirel University Journal of Natural and Applied Science, S:18(1), ss.1-7. KLEIN, J.P. ve MOESCHBERGER, M.L. (1997), Survival Analysis: Techniques for Censored and Truncated Data, Springer-Verlag, New York. KLEINBAUM, D.G. ve KLEIN, M. (2005), Survival Analysis: A Self-Learning text, New York, Springer. LEE, E.T. ve Wang, J.W. (2003), Statistical Methods for Survival Data Analysis, New York: Wiley. LETON, E. ve ZULUAGA, P. (2001),” Equivalence Between Score and Weighted Tests for Survival Curves,” Commun. Statist.–Theory Meth., S:30(4), ss.591-608. LEVIN, H. M. (1972), “The costs to the nation of inadequate education” (Report to the Select Committee on Equal Educational Opportunity of the United States Senate, January). Washington, DC: U.S. Government Printing Office. NARDI, M., ve SCHEMPER, M. (2003), “Comparing Cox and Parametric Models in Clinical Studies”, Statistics in Medicine, S:22, ss.3597-3610. NATRIELLO, G. (1987), School Dropouts: Patterns and Policies, New York: Teachers College Press. O’QUIGLEY, J. ve STARE, J. (2002), “Proportional Hazards Models with Frailties and Random Effects”, Statistics in Medicine, S:21, ss.3219-3233. ORBE, J., FERREIRA, E. ve NUNEZ-ANTON, V. (2002), “Comparing Proportional Hazards and Accelerated Failure Time Models for Survival Analysis”, Statistics in Medicine, S:21, ss.3493-3510. QUI, J. (2009), “Comparison of proportional hazards and accelerated failure time models” University of Saskatchewan, Department of Mathematics and Statistics, Saskatoon, Saskatchewan, Canada. PANKRATZ, V. S., DE ANDRADE, M. ve THERNAU, T. M. (2005), “Random Effects Cox Proportional Hazard Model: General Variance Components Methods for Time-To-Event Data”, Genetic Epidemology, S:28, ss.97-109. PORTER, A. M. (1990), “Undergraduate Completion and Persistence at Four-Year Colleges and Universities”, Reports-Research, Washington, DC: National Institute of Independent Colleges and Universities. RADCLIFFE, P. M., HUESMAN, R.L. Jr. ve KELLOGG, J.P. (2006), “Identifying Students at Risk: Utilizing Survival Analysis to Study Student Athlete Attrition”, Retrieved from the University of Minnesota Digital Conservancy, http://purl.umn.edu/159769. SCHOENFELD, D. (1982), “Partial Residuals For The Proportional Hazards Model”, Biometrika, S:69, ss.551-55. SPADY, W. (1970), “Drop-Outs From Higher Education: An Interdisciplinary Review And Synthesis”, Interchange, S:1, ss.64–85. TARONE, R.E. ve WARE, J. (1977), “On distribution-free tests for equality of survival distributions”, Biometrika, S:64(1), ss.156–160. TERENZINI, P. T. ve PASCARELLA, E. T. (1980), “Towards The Validation of Tinto's Model of College Student Attrition: A Review Of Recent Studies”, Research in Higher Education, S:12(3), ss.271-282 TINTO, V. (1975), “Dropout From Higher Education: A Theoretical Synthesis Of Recent Research”, Review of Educational Research, S:45(1), ss.89–125. TINTO, V. (1982), “Limits in Theory and Practice in Student Attrition”, Journal of Higher Education, S:53, ss.687-700. VAUPEL, J.W., MANTON, K. ve STALLARD, E. (1979), “The Impact of Heterogeneity in İndividual Frailty On The Dynamics of Mortality”, Demography, S:16, ss.439–454. WATSON, C. (1974), “Focus on dropouts”, Toronto, Canada: Ontario Institute for the Study of Education. WEI, L.J. (1992), “The Accelerated Failure Time Model: A Useful Alternative To The Cox Regression Model İn Survival Analysis”, Statistics in Medicine, S:11, ss.1871-1879. WEIS, L., Farrar, E., & Petrie, H. G. (1989), “Dropouts From School: Issues, Dilemmas, And Solutions”, Albany, NY: State University of New York. WILLETT, J.B. ve SINGER, J.D. (1991), “From Whether To When: New Methods For Studying Student Dropout And Teacher Attrition”, Review of Educational Research, S:61, ss.407–450. ZIOLKOWSKI, T. (1990), “The PhD Squid”, American Scholar, S:59(2), ss.177-195. ZWICK, R. ve SKLAR, J. (2005), “Predicting College Grades And Degree Completion Using High School Grades And Sat Scores: The Role Of Student Ethnicity And First Language”, American Educational Research Journal, S:42, ss.439–464.