Date Thesis Awarded

5-2023

Access Type

Honors Thesis -- Access Restricted On-Campus Only

Degree Name

Bachelors of Science (BS)

Department

Mathematics

Advisor

Lawrence Leemis

Committee Members

Heather Sasinowska

Carl Moody

Abstract

Kaplan and Meier’s 1958 paper developed a nonparametric estimator of the survivor function from a right-censored data set. We devise two algorithms for determining the support values and calculating the support size for the Kaplan–Meier Product–Limit Estimator (KMPLE). We also derived a generalized formula to calculate the associated probability mass function for all sample sizes. The probability mass function is then applied to confirm the bias in the KMPLE as well as calculating the actual coverage functions for different confidence intervals. Finally, we investigated the concept of competing risks in a right-censored data set.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Available for download on Monday, May 08, 2028

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