The Estimation of (Covid-19) Cases in Kurdistan Region Using Nelson Aalen Estimator

  • Sami A. Obed Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region - F.R. Iraq https://orcid.org/0000-0002-2866-5886
  • Parzhin A. Mohammed Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region, Iraq. https://orcid.org/0000-0003-2998-9871
  • Dler H. kadir Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region, Iraq; (2) Department of Business Administration, Cihan University-Erbil, Iraq http://orcid.org/0000-0001-5196-4457
Keywords: Estimator, Survival Analysis, Covied-19, Nelson Allen Estimator, Death

Abstract

It is described how the Nelson–Aalen estimator may be used to control the rate of a nonparametric estimate of the cumulative hazard rate function based on right censored as well as left condensed survival data, furthermore how the Nelson–Aalen estimator can be utilized to estimate various amounts. This technique is mostly applied to survival data and product quality data similar to the incorporated relative mortality in a multiplicative model with outer rates and the cumulative infection rate in a straightforward epidemic model. It is shown that tallying measures produce a structure that permits to a brought together treatment of all these different conditions, and the main little and massive sample properties of the assessor are summarized. This estimator is a weighted average of the Nelson-Aalen reliability estimates over two time periods. The suggested estimator's suitability and utility in model selection are reviewed. And a real-world dataset is evaluated to demonstrate the proposed estimator's suitability and utility. This work proposes a simple and nearly unbiased estimator to fill this gap. The information was gathered from the Ministry of Health's website between October 1, 2020, and February 28, 2021. The results of the Nelson Allen Estimator demonstrated that the odds of surviving were higher during a short period of time after being exposed to the virus. As time passes, the possibilities become slimmer. The closer the estimate comes to value 1 from 0.5 upward, the greater the chances of surviving the infection.

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Author Biographies

Sami A. Obed, Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region - F.R. Iraq

I graduated from Salahaddin University – Erbil in 2013  College of Administration & Economics  \ Statistics Department  from 2013 to 2016 worked  Assistant Researcher in Statistics Department . In 2019I have earned master's degree in the Department of Statistics college of Administration and Economy, University of Salahaddin and through these years ( 2020-2021) I studied the third stage students Time series at the Department of  Economics, and, so far, I am working as an assistant teacher in the Department of Statistics

Parzhin A. Mohammed, Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region, Iraq.

I was awarded a B.Sc. from the University of Salahaddin in College of Administration & Economics \ Statistics Department in 2012. I also received a M.Sc. degree in applied statistics at Salahaddin University in 2016. I am an assistant Lecture in the Department of statistics.

Dler H. kadir, Department of Statistics, College of Administration and Economics, Salahaddin University-Erbil, Kurdistan Region, Iraq; (2) Department of Business Administration, Cihan University-Erbil, Iraq

I was awarded a B.Sc. in Statistics from the University of Salahaddin in 2002. I also received a M.Sc. degree in applied statistics at Sulaymaniyah University in 2007. I was awarded a PhD from Sheffield University in 2018. My research interest in Bayesian inference, MCMC, Statistical Modeling, Quality control charts and Time series analysis

References

D. Abbas. Analysis of breast cancer data using Kaplan-Meier survival analysis. Journal of Kufa for Mathematics and Computer, vol. 1, no. 6, pp. 7-14, 2012.

T. D.Bluhmki. The wild bootstrap for multivariate Nelson-Aalen estimators. Lifetime Data Analysis, vol. 25, no. 1, pp. 97-127, 2019.

R. L. Cao. Presmoothed Kaplan-Meier and Nelson-Aalen estimators. Journal of Nonparametric Statistics, vol. 17, no. 1, pp. 31-56, 2005.

C. A. El-Nouty. The presmoothed Nelson-Aalen estimator in the competing risk model. Communications in Statistics-Theory and Methods, vol. 33, no. 1, pp. 135-151, 2005.

D. A. Luo. Bias and mean-square error for the Kaplan-Meier and Nelson-Aalen estimators. Journal of Nonparametric Statistics, vol. 3, no. 1, pp. 37-51, 1993.

R. A. Jiang. A bias-corrected Nelson-Aalen estimator. In: IOP Conference Series: Materials Science and Engineering. Vol. 1043. Changsha: IOP Publishing, p. 022013, 2021.

A. A. Winnett. Adjusted Nelson-Aalen estimates with retrospective matching. Journal of the American Statistical Association, vol. 97, no. 457, pp. 245-256, 2002.

A. S. Rossa. The Nelson-Aalen and Kaplan-Meier estimators under a sequential sampling scheme. Communications in Statistics Theory and Methods, vol. 38, no. 16-17, pp. 3077-3098, 2009.

H. A. Zhang. On Nelson-Aalen type estimation in the partial Koziol-Green model. Statistics, vol. 44, no. 5, pp. 455-465, 2010

Published
2021-09-30
How to Cite
1.
Obed S, Mohammed P, kadir D. The Estimation of (Covid-19) Cases in Kurdistan Region Using Nelson Aalen Estimator. cuesj [Internet]. 30Sep.2021 [cited 20Oct.2021];5(2):24-1. Available from: https://journals.cihanuniversity.edu.iq/index.php/cuesj/article/view/448
Section
Research Article