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Orantısız hazardlar için parametrik ve yarı parametrik yaşam modelleri

Year 2008, Volume: 1 Issue: 3, 125 - 134, 01.09.2008

Abstract

References

  • Arjas, E., (1988), A graphical method for assessing goodness of fit in Cox’s proportional hazards model, Journal of the American Statistical Association, 83, 204-212.
  • Ata, N., Sözer, M.T., (2007), Cox Regression Models with Nonproportional Hazards Applied to Lung Cancer Survival Data, Hacettepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, Matematik ve İstatistik Dergisi, B Serisi, 36(2), 157-167.
  • Bender R., Augustin, T., Blettner, M., (2005), Generating survival times to simulate Cox proportional hazards models, Statistics in Medicine, vol.24, pp.1713-1723.
  • Cox, D.R., (1972), Regression models and life-tables, Journal of the Royal Statistical Society, Series B, 34, 187-220.
  • Cox, D.R., Snell, E.J., (1968), A General Definition of Residuals, Journal of the Royal Statistical Society, Series B, 30, 248-275.
  • Collett, D., (1994), Modelling Survival Data in Medical Research, Chapman&Hall, UK.
  • Efron, B., (1977), The Efficiency of Cox’s Likelihood Function for Censored Data, Journal of the American Statistical Association, 72, 557-565.
  • Kalbfleisch, J.D. , Prentice,R.L., (1980), The Statistical Analysis of Failure Time Data, Wiley, New York.
  • Klein, J.P., Moeschberger, M.L., (1997), Survival Analysis Techniques for Censored and Truncated Data, Springer, New York.
  • London, D., (1997), Survival Models and Their Estimation, Actex Publications, USA.
  • Lee, E.T., Wang, J.W., (2003) Statistical Methods for Survival Data Analysis, Wiley&Sons, New York.
  • Nardi, A., Schemper, M., (2003), Comparing Cox and Parametric Models in Clinical Studies, Statistics in Medicine, vol.22, pp.3597-3610.
  • Oakes, D., (1977), The Asymtotic Information In Censored Survival Data, Biometrika, 64, 441-448.
  • Schoenfeld, D., (1982), Partial residuals for the proportional hazards model, Biometrika, Vol.69, pp.551-55.
  • Therneau, T.M., Grambsch, P.M., (2000), Modelling Survival Data: Extending the Cox Model, Springer, New York.

Orantısız hazardlar için parametrik ve yarı parametrik yaşam modelleri

Year 2008, Volume: 1 Issue: 3, 125 - 134, 01.09.2008

Abstract

Yaşam verileri için en çok kullanılan regresyon modeli Cox regresyon modelidir. Bu model orantılı hazardlar varsayımına karşı duyarlıdır. Bu varsayımın sağlanmadığı durumlarda farklı yaşam modellerinin kullanılması önerilmektedir. Bu çalışmada, orantılı hazardlar varsayımının sağlanmadığı durumlarda parametrik yaşam modelleri (üstel, weibull, log-lojistik, log-normal, Gompertz, Gamma regresyon modelleri) ve yarı parametrik yaşam modelleri (Cox regresyon modeli ve uzanımları) incelenmiştir. Orantılı hazardlar varsayımını sağlamayan gerçek yaşam verileri kullanılarak, parametrik ve yarı parametrik yaşam modellerinin uygulaması yapılmıştır

References

  • Arjas, E., (1988), A graphical method for assessing goodness of fit in Cox’s proportional hazards model, Journal of the American Statistical Association, 83, 204-212.
  • Ata, N., Sözer, M.T., (2007), Cox Regression Models with Nonproportional Hazards Applied to Lung Cancer Survival Data, Hacettepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, Matematik ve İstatistik Dergisi, B Serisi, 36(2), 157-167.
  • Bender R., Augustin, T., Blettner, M., (2005), Generating survival times to simulate Cox proportional hazards models, Statistics in Medicine, vol.24, pp.1713-1723.
  • Cox, D.R., (1972), Regression models and life-tables, Journal of the Royal Statistical Society, Series B, 34, 187-220.
  • Cox, D.R., Snell, E.J., (1968), A General Definition of Residuals, Journal of the Royal Statistical Society, Series B, 30, 248-275.
  • Collett, D., (1994), Modelling Survival Data in Medical Research, Chapman&Hall, UK.
  • Efron, B., (1977), The Efficiency of Cox’s Likelihood Function for Censored Data, Journal of the American Statistical Association, 72, 557-565.
  • Kalbfleisch, J.D. , Prentice,R.L., (1980), The Statistical Analysis of Failure Time Data, Wiley, New York.
  • Klein, J.P., Moeschberger, M.L., (1997), Survival Analysis Techniques for Censored and Truncated Data, Springer, New York.
  • London, D., (1997), Survival Models and Their Estimation, Actex Publications, USA.
  • Lee, E.T., Wang, J.W., (2003) Statistical Methods for Survival Data Analysis, Wiley&Sons, New York.
  • Nardi, A., Schemper, M., (2003), Comparing Cox and Parametric Models in Clinical Studies, Statistics in Medicine, vol.22, pp.3597-3610.
  • Oakes, D., (1977), The Asymtotic Information In Censored Survival Data, Biometrika, 64, 441-448.
  • Schoenfeld, D., (1982), Partial residuals for the proportional hazards model, Biometrika, Vol.69, pp.551-55.
  • Therneau, T.M., Grambsch, P.M., (2000), Modelling Survival Data: Extending the Cox Model, Springer, New York.
There are 15 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

N. Ata This is me

D. Karasoy This is me

M. T. Sözer This is me

Publication Date September 1, 2008
Published in Issue Year 2008 Volume: 1 Issue: 3

Cite

IEEE N. Ata, D. Karasoy, and M. T. Sözer, “Orantısız hazardlar için parametrik ve yarı parametrik yaşam modelleri”, JSSA, vol. 1, no. 3, pp. 125–134, 2008.