Modified Cox-Snell Residuals in Evaluating Gompertz Regression Model with Censored Data

Authors

  • Nur Niswah Naslina Azid Universiti Putra Malaysia, Malaysia Author

DOI:

https://doi.org/10.61841/dnaaav05

Keywords:

Gompertz Model,, Right Censored Covariate, Cox-Snell Residuals, Simulation.

Abstract

In this research, a two parameter Gompertz parametric survival model was extended to incorporate with covariate in the presence of right censored and uncensored data. The estimation procedure was studied at different sample sizes and censoring percentiles via simulation methodology. Statistically, the simulated data were assessed using the bias, standard error and root mean square error of the parameter estimates for the Gompertz regression model. Subsequently, various combinations of sample sizes and censoring levels were employed to evaluate the performance of the proposed modifications to the Cox-Snell residuals for both censored and uncensored observations. The results clearly indicate that the estimates perform well when the censoring degrees are lower, and the sample sizes are greater. The performance of the modified Cox-Snell residuals based on harmonic mean outperformed than the other approaches.

 

Downloads

Download data is not yet available.

References

1. Chen, Z. (1997). Parameter Estimation of the Gompertz Population. Biometrical Journal, 39(1), 117-124.

2. Cox, D.R., & Snell, E.J. (1968). A General Definition of Residuals. Journal of the Royal Statistical Society

Series B (Methodological), 30(2), 248-275.

3. Dey, S., Moala, F.A., & Kumar, D. (2018). Statistical properties and different methods of estimation of

Gompertz distribution with application. Journal of Statistics and Management Systems, 21(5), 839–876.

4. Garg, M.L., Rao, B.R., & Redmond, C.K. (1970). Maximum-Likelihood Estimation of the Parameters of

the Gompertz Survival Function. Journal of the Royal Statistical Society Series C (Applied Statistics), 19(2), 152-159.

5. Gompertz, B. (1825). On the Nature of the Function Expressive of the Law of Human Mortality and on a New Mode of Determining the Value of Life Contingencies. Philosophical Transactions of the Royal

Society of London, 115, 513-583.

6. Gordon, N.H. (1990). Maximum likelihood estimation for mixtures of two gompertz distributions when

censoring occurs. Communications in Statistics - Simulation and Computation, 19(2), 733–747.

7. Ieren, T.G., Kromtit, F.M., Agbor, B.U., Eraikhuemen, I.B., & Koleoso, P.O. (2019). A Power Gompertz

Distribution: Model, Properties and Application to Bladder Cancer Data. Asian Research Journal of Mathematics, 15(2), 1-14.

8. Kiani, K., & Arasan, J. (2013). Gompertz model with time-dependent covariate in the presence of interval-

, right- and left-censored data. Journal of Statistical Computation and Simulation, 83(8), 1472-1490.

9. Kiani, K., Arasan, J., & Midi, H. (2012). Interval estimations for parameters of gompertz model with time

dependent covariate and right censored data. Sains Malaysiana, 41(4), 471-480.

10. Lenart, A. (2012). The moments of the Gompertz distribution and maximum likelihood estimation of its

parameters. Scandinavian Actuarial Journal, 2014(3), 255–277.

11. Makany, R. (1991). A Theoretical Basis for Gompertz’s Curve. Biometrical Journal, 33(1), 121–128.

12. Witten, W., & Satzer, W. (1992). Gompertz survival model parameters: Estimation and sensitivity.

Applied Mathematics Letters, 5(1), 7-12.

13. Wu, J.-W., Hung, W.-L., & Tsai, C.-H. (2004). Estimation of the parameters of the Gompertz distribution

using the least squares method. Applied Mathematics and Computation, 158(1), 133–147.

Downloads

Published

30.06.2020

How to Cite

Azid, N. N. N. (2020). Modified Cox-Snell Residuals in Evaluating Gompertz Regression Model with Censored Data. International Journal of Psychosocial Rehabilitation, 24(6), 2315-2329. https://doi.org/10.61841/dnaaav05