Fitting Cox Proportional Model and Poisson Regression Model to Data of Patients with Stomach Cancer in Erbil-Kurdistan/Iraq
DOI:
https://doi.org/10.25156/ptjhss.v4n2y2023.pp127-136Keywords:
Survival Analysis, cox proportional model, Poisson regression model, Akaike Information Criterion (AIC), stomach cancer.Abstract
Abstract— This study aims to fitting two models where allow the response variable to be the length of time (months) to data of patients with stomach cancer; cox proportional model and Poisson regression model, for modeling and identifying the affecting factors of stomach cancer patients. The
study was conducted between January 1, 2016 until December 31, 2020 for all patients with stomach cancer at Nanakali Main Hospital for Cancer in the Kurdistan Region of Iraq - Erbil.
The results indicated that, the models have not reached to the same variables that have an impact on our data of patients with stomach cancer data in Erbil city. Moreover, according to the results the Poisson regression fitted data set very well depending on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values, the best model will be identified by the ones with smaller values. The data analyses of stomach cancer are done by using statistical programs (Mat-lab V.14 , SPSS V. 25 and STATGRAPHICS V. 19).
Downloads
References
- References
ADETI , F., 2016. Modelling count out comes from dental caries in adults: A comparision of completing statistics models. Kwame Nkrumah University of Scince and technologu,Kumas, pp. 59-60.
AGRESTI, A., 2006. An Introduction to Categorical Data Analysis. s.l.:2007 John Wiley & Sons, Inc.
AHMAD, S. M., 2019. Predicting Cancer Survival Patients using Wavelets with Cox Regression Model. p. 41.
ALJAS, E., 1988. A Graphical Method for Assessing Goodness of Fit in Cox's Proportional Hazards Model.. Journal of the American Statistical Association, 83(401), pp. 204-212.
AMERICAN CANCER SOCITY, 2022. cancer A-Z. [Online]
Available at: https://www.cancer.org/cancer/stomach-cancer/about/what-is-stomach-cancer.html#references
Anon., 2016. Poisson regression. NCSS, LLC. All Rights Reserved., pp. https://ncss-wpengine.netdna-ssl.com/wp-content/themes/ncss/pdf/Procedures/NCSS/Poisson_Regression.pdf.
CAMERON, A. C. & TRIVEDI, P. K., 2012. Regression analysis of count data. In: Event history analysis with R. s.l.:Cambridge university press.Brostrom.
C. D., 2003. Modling Survival Data For Medical Research. London Uk Chapman Hall.
CONSUL, P. C. & FAMOYE, F., 1992. Generalized Poisson regression model. pp. 89-109.
Coxe, S., West, S. G. & Aiken, L. S., 2009. The analysis of count data: A gentle introduction to Poisson regression and its alternatives. Journal of Personality Assessment, pp. 121-136.
FOX, J., 2014. Introduction to Survival analysis. sociology 761.
HOUT, A. V. D., 2017. Multi-State Survival Models for Interval-censored data. London: Taylor & Francis Group CRC Press.
I. K., 2019. Overall And Relative Survival For Cancer Patients. Unverstetet I Stavanger, P. 7
KLEINBUM , D. G. & KLEIN, M., 2012. Survival analysis. In: A self-learning text (3rd ed.). New york: Springer.
KOROSTELEVA, O., n.d. Survival analysis. In: s.l.:s.n., p. 60.
LEE, E. T. & JOHN, W. W., 2003. Statistical methods for survival data analysis. p. 476.
LOKESHMARAN A, &. ,. R. E., 2013. BAYESIAN VARIABLE SELECTION FOR COX’S REGRESSION MODEL. Asia Pacific Journal of Research, pp. 11 - 23.
Montgomery, D. C., Peck, E. A. E. A. & Vining, G. G., 2006. Introduction to Linear Regression Analysis (4th ed.). Hoboken: John Wiley & Sons. s.l.:JOURNAL NAME: Engineering, Vol.6 No.12, November 13, 2014.
MOREAU, T., O'QUIGLEY, J. & MESBAH, M., 1985. A Global Goodness‐Of‐Fit Statistic for the Proportional Hazards Model. Journal of the Royal Statistical Society., pp. 212-218.
PARZEN , M. & LIPSITZ, S. R., 1999. A Global Goodness-of-Fit Statistic for Cox Regression ModelS. Biometrics, pp. 580-584.
SCHMIDT, P. & WITTE, A. D., 1998. Predicting Recidivism Using Survival Models. 1st ed. London: Springer verlag.
SHINGLETON, J. S., 2012. CRIME TREND PREDICTION USING REGRESSION MODELS FOR SALINAS. MONTEREY, pp. 22-23.
SINGER, J. D. & WILLETT , J. B., 1991. Using Survival Analysis When Designing and Analyzing Longitudinal Studies of Duration and the timing of Events. s.l.:Psychological Bulletin.
WEI, L. J., 1984. Testing Goodness of Fit for Proportional Hazards Model with Censored Observations. Journal of the American Statistical Association, pp. 649-652.
فتيحة، ب.، 2015. تقدير مدة البحث عن الشغل لحاملي شهادات تكوين المهني باستعمال نموذج الأخطار النسبية. مجلة العلوم الاقتصاد والتسيير والتجارة (جامعة بغداد)، pp. 11-33.
Polytechnic J. Hum. Soc. Sci.: A Periodical Open Access Scientific Journal