Research Article
BibTex RIS Cite

Cox regressiom model and an application to lıng anser data

Year 2008, Volume: 1 Issue: 1, 16 - 23, 01.03.2008

Abstract

In medical science, in investigating the
survival data of epidemic diseases and chronic diseases and determining the
factors which affects these diseases, Cox regression model for survival
analysis has gained widespread attention.
In this paper, Cox regression model is
presented and using this model risk factors affecting relapse  of  lung
cancer is determined.

References

  • Collate, D. (1994), Modelling Survival Data in Medical Research, Chapman and Hall, London.
  • Cox, D. R. (1972), Regression Models and Life Tables, Journal of Royal Statistical Society, 34, 187-202.
  • Cox, D. R. and Oakes, D. (1984), Analysis of Survival Data, Chapman and Hall, London.
  • Johnson, R.E. and Johnson, N. (1980), Survival models and data analysis, John Wiley and Sons, New York.
  • Kalbfleisch, J. D. and Prentice, R. L. (1973), Marjinal Likelihoods Based on Cox’s
  • Regression and Life Model, Biometrika, 60, 267-279. Kaplan, E. L. and Meier, P. (1958), Nonparametric Estimation From Incomplete
  • Observations, Journal of the American Statistical Association, 53, 457-481. Lawless, J. F. (1982), Statistical Models and Methods for Lifetime Data, John Wiley and Sons, New York.
  • Peterson, A.P. (1977), Expressing the Kaplan-Meier estimator as a function of empirical survival functions, J.
  • Amer. Statist. Assoc., 72, 854-858. Prentice, R.L. (1973), Exponential survival with censoring and explanatory variables, Biometrika, 61, 539-544.

Cox Regresyon Modeli ve Akciğer Kanseri Verileri İle Bir Uygulama

Year 2008, Volume: 1 Issue: 1, 16 - 23, 01.03.2008

Abstract

Tıpta, salgın hastalıklara ve kronik hastalıklara ilişkin verilerin incelenmesi ve bu hastalıkları etkileyen faktörlerin saptanması için yaşam çözümlemesinde Cox regresyon modeli oldukça önemlidir. Bu çalışmada, Cox regresyon modeli tanıtılmış ve bu model kullanılarak akciğer kanserinde nüksü etkileyen risk faktörleri belirlenmiştir

References

  • Collate, D. (1994), Modelling Survival Data in Medical Research, Chapman and Hall, London.
  • Cox, D. R. (1972), Regression Models and Life Tables, Journal of Royal Statistical Society, 34, 187-202.
  • Cox, D. R. and Oakes, D. (1984), Analysis of Survival Data, Chapman and Hall, London.
  • Johnson, R.E. and Johnson, N. (1980), Survival models and data analysis, John Wiley and Sons, New York.
  • Kalbfleisch, J. D. and Prentice, R. L. (1973), Marjinal Likelihoods Based on Cox’s
  • Regression and Life Model, Biometrika, 60, 267-279. Kaplan, E. L. and Meier, P. (1958), Nonparametric Estimation From Incomplete
  • Observations, Journal of the American Statistical Association, 53, 457-481. Lawless, J. F. (1982), Statistical Models and Methods for Lifetime Data, John Wiley and Sons, New York.
  • Peterson, A.P. (1977), Expressing the Kaplan-Meier estimator as a function of empirical survival functions, J.
  • Amer. Statist. Assoc., 72, 854-858. Prentice, R.L. (1973), Exponential survival with censoring and explanatory variables, Biometrika, 61, 539-544.
There are 9 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

D. Karasoy

Publication Date March 1, 2008
Published in Issue Year 2008 Volume: 1 Issue: 1

Cite

IEEE D. Karasoy, “Cox Regresyon Modeli ve Akciğer Kanseri Verileri İle Bir Uygulama”, JSSA, vol. 1, no. 1, pp. 16–23, 2008.