Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data

Yıl: 2019 Cilt: 32 Sayı: 1 Sayfa Aralığı: 318 - 331 Metin Dili: İngilizce İndeks Tarihi: 20-02-2020

Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data

Öz:
This study is aimed to obtain an appropriate logistic regression model based on the bootstrapmethods. For this purpose, two bootstrap methods called bootstrap I and bootstrap II are given toobtain the estimations of parameters and standard errors. Traditional logistic regression iscompared with the bootstrap I and bootstrap II methods in terms of the parameter estimations andstandard errors. It has been found that the standard errors of the parameter estimations for thebootstrap I model are smaller than others. Also, the average widths of confidence interval basedon bootstrap I model are narrower than the logistic regression and bootstrap II. It is seen that, thesimulation study based on different sample sizes supports these results. It can be said that thebootstrap I model based on resampling of errors term is the best in estimating coronary arterydisease.
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  • Alpar, R., Uygulamalı Çok Değişkenli İstatistiksel Yöntemler, Detay Yayıncılık, Ankara; (2011).
  • Kleinbaum, D., Klein, M., Logistic Regression- A Self Learning Text, II ed. New York, NY: Springer; (2002).
  • Berkson, J., “Application of the logistic function to bio-assay”, J. Am. Stat. Assoc., 39(227): 357–65, (1944).
  • Lim, E., Ali, Z.A., Barlow, C.W., Jackson, C.H., Hosseinpour, A.R., Halstead, J.C., et al., “A simple model to predict coronary disease in patients undergoing operation for mitral regurgitation”, Ann. Thorac. Surg., 75(6):1820–5, (2003).
  • Vupa, O., Çelikoğlu, C., “Model building in logistic regression models about lung cancer data”, Anadolu Univ. J. Sci. Tech., 7(1): 127–41, (2006).
  • Coşkun, S., Kartal, M., Coşkun, A., Bircan, H., “Lojistik regresyon analizinin incelenmesi ve diş hekimliğinde bir uygulaması”, Cumhuriyet Üniversitesi Diş Hekimliği Fakültesi Dergisi, 7(1): 42–50, (2004)
  • Hirashiki, A., Yamada, Y., Murase, Y., Hirashiki, A., Yamada, Y., Murase, Y., “Association of gene polymorphisms with coronary artery disease in low- or high-risk subjects defined by conventional risk factors”, J. Am. Coll. Cardiol., 42(8): 1429–37, (2003).
  • Horibe, H., Yamada, Y., Ichihara, S., Watarai, M., Yanase, M., Takemoto, K., et al., “Genetic risk for restenosis after coronary balloon angioplasty”, Atherosclerosis, 174(1): 181–7, (2004).
  • Çolak, C., Çolak, M.C., Orman, M.N., “The Comparison of logistic regression model selection methods for the prediction of coronary artery disease”, The Anatol. J. Cardiol., 7(1): 6–12, (2007).
  • Atabey, Ö. “Lojistik regresyon modeli ve geriye doğru eliminasyon yöntemiyle değişken seçiminin hipertansiyon riski üzerine uygulamasında bootstrap yöntemi”, Gazi Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, Ankara, (2010).
  • Yan, T., Zhang, G.X., Li, B.L., Han, L., Zang, J.J., Li, L., Xu, Z.Y., “Prediction of coronary artery disease in patients undergoing operations for rheumatic aortic valve disease”, Clin. Cardiol., 35(11): 707-11, (2012) .
  • Gündoğdu, F., Özdemir, Ö., Sevimli, S., Açıkel, M., Pirim, İ., Karakelleoğlu, Ş., et al., “The relationship between interleukin-6 polymorphism and the extent of coronary artery disease in patients with acute coronary syndrome”, Arch. Turk. Soc. Cardiol., 35(5): 278–83, (2007).
  • Yin, Y., Li, J., Zhang, M., Wang, J., Li, B., Liu, Y., et al., “Influence of interleukin-6 gene -174g>c polymorphism on development of atherosclerosis: a meta-analysis of 50 studies involving, 33.514 subjects”, Gene, 529: 94–103, (2013).
  • Elsaid, A., Abdel-Aziz, A.F., Elmougy, R., Elwaseef, A.M., “Association of polymorphisms G (-174) C in IL-6 gene and G (-1082) A in IL-10 gene with traditional cardiovascular risk factors in patients with coronary artery disease”, Indian J. Biochem. Biophys., 51: 282–92, (2014).
  • Roger, V.L., Go, A.S., Lloyd-Jones, D.M., Benjamin, E.J., Berry, J.D., Borden, W.B., et al., “Executive summary: heart disease and stroke statistics-2012 update: a report from the american heart association”, Circ., 125(1): 188–97, (2012).
  • Onat, A., Yüksel, M., Köroğlu, B., Gümrükçüoğlu, H.A., Aydın, M., Çakmak, H.A., “Turkish adult risk factor study survey 2012: overall and coronary mortality and trends in the prevalence of metabolic syndrome”, Arch. Turk. Soc. Cardiol., 41: 373–8, (2013).
  • Anderson, D.R., Poterucha, J.T., Mikuls, T.R., Duryee, M.J., Garvin, R.P., Klassen, L.W., et al., “IL6 and its receptors in coronary artery disease and acute myocardial infarction”, Cytokine, 62(3): 395- 400, (2013).
  • Teixeira, B.C., Lopes, A.L., Macedo, R.C.O., Correa, C.S., Ramis, T.R., Ribeiro, J.L., et al., “Inflammatory markers, endothelial function and cardiovascular risk”, J. Vascul. Brasileiro, 13(2): 108–15, (2014).
  • Hosmer, D., Lemeshow, S., Sturdıvant, R., Applied Logistic Regression. Canada: Wiley&Sons Publications, (2013).
  • Mammen, E., When Does Bootstrap Work?. USA: Springer-Verlag New York, (1992).
  • Özdemir, A., “Doğrusal olmayan regresyonda asimptotik yöntemle bootstrap örneklemesi”, Yüksek Lisans Tezi, Yıldız Teknik Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul, (2011).
  • Aktükün, A. “Asal bileşenler analizinde bootstrap yaklaşımı”, İstanbul Üniversitesi İktisat Fakültesi Ekonomi ve İstatistik Dergisi, 1: 1–11, (2005).
  • Chernick, M.R., Bootstrap Methods. (2nd edition). Canada: John Wiley and Sons, (1999).
  • Efron, B., Tibshirani RJ. An Introduction to the Bootstrap. Chapman & Hall, New York USA, (1993).
  • Shao, J., Tu D, The Jacknife and Bootstrap, Spinger-Veriag, Newyork, (1995).
  • Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., Tatham, R.,L. Multivariate Data Analysis, Upper Saddle River, NJ: Pearson Prentice Hall, (2006).
  • Bendel, R.B., Afifi, A.A., “Comparison of stopping rules in forward stepwise regression”, J. Am. Stat. Assoc., 72(357): 46–53, (1977).
  • Mickey, R.M., Greenland, S., “The impact of confounder selection criteria on effect estimation”, Am. J. Epidemiol., 129(1): 125–37, (1989).
  • Stute, W., Manteiga, W. G., Quindimil, M. P. “Bootstrap approximations in model checks for regression”, Journal of the American Statistical Association, 93(441):141–9, (1998).
  • Karadağ, M., “Karar ağaçları ile lojistik regresyon analizinin performanslarının simülasyon çalışması ile karşılaştırılması”, Yüksek Lisans Tezi, Trakya Üniversitesi, Sağlık Bilimleri Enstitüsü, Edirne, (2014)
APA AKYÜZ H, GAMGAM H (2019). Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data. , 318 - 331.
Chicago AKYÜZ HAYRIYE ESRA,GAMGAM HAMZA Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data. (2019): 318 - 331.
MLA AKYÜZ HAYRIYE ESRA,GAMGAM HAMZA Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data. , 2019, ss.318 - 331.
AMA AKYÜZ H,GAMGAM H Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data. . 2019; 318 - 331.
Vancouver AKYÜZ H,GAMGAM H Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data. . 2019; 318 - 331.
IEEE AKYÜZ H,GAMGAM H "Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data." , ss.318 - 331, 2019.
ISNAD AKYÜZ, HAYRIYE ESRA - GAMGAM, HAMZA. "Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data". (2019), 318-331.
APA AKYÜZ H, GAMGAM H (2019). Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data. Gazi University Journal of Science, 32(1), 318 - 331.
Chicago AKYÜZ HAYRIYE ESRA,GAMGAM HAMZA Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data. Gazi University Journal of Science 32, no.1 (2019): 318 - 331.
MLA AKYÜZ HAYRIYE ESRA,GAMGAM HAMZA Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data. Gazi University Journal of Science, vol.32, no.1, 2019, ss.318 - 331.
AMA AKYÜZ H,GAMGAM H Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data. Gazi University Journal of Science. 2019; 32(1): 318 - 331.
Vancouver AKYÜZ H,GAMGAM H Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data. Gazi University Journal of Science. 2019; 32(1): 318 - 331.
IEEE AKYÜZ H,GAMGAM H "Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data." Gazi University Journal of Science, 32, ss.318 - 331, 2019.
ISNAD AKYÜZ, HAYRIYE ESRA - GAMGAM, HAMZA. "Comparison of Binary Logistic Regression Models Based on Bootstrap Method: An Application on Coronary Artery Disease Data". Gazi University Journal of Science 32/1 (2019), 318-331.