Finite sample and asymptotic distributions of a statistic for sufficient follow‐up in cure models

Author:

Maller Ross1ORCID,Resnick Sidney2,Shemehsavar Soudabeh3

Affiliation:

1. Research School of Finance, Actuarial Studies & Statistics Australian National University Canberra ACT 0200 Australia

2. School of Operations Research & Information Engineering Cornell University Ithaca New York U.S.A.

3. College of Science, Health Engineering & Education, Murdoch University and School of Mathematics, Statistics & Computer Sciences University of Tehran Tehran Iran

Abstract

AbstractThe existence of immune or cured individuals in a population and whether there is sufficient follow‐up in a sample of censored observations on their lifetimes to be confident of their presence are questions of major importance in medical survival analysis. Here we give a detailed analysis of a statistic designed to test for sufficient follow‐up in a sample. Assuming an i.i.d. censoring model, we obtain exact finite‐sample and asymptotic distributions for the statistic, and use these to calculate the power of a test based on it. A particularly useful finding is that the asymptotic distribution of the test statistic is parameter‐free in the null case when follow‐up is insufficient. The methods are illustrated with application to a glioma cancer dataset.

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference36 articles.

1. Amdahl J.(2020).flexsurvcure: Flexible parametric mixture and non‐mixture cure models for time‐to‐event data https://cran.r‐project.org/web/packages/flexsurvcure/flexsurvcure.pdf.

2. Cure Models in Survival Analysis

3. Review and implementation of cure models based on first hitting times for Wiener processes

4. Survival Curve for Cancer Patients Following Treatment

5. Maximum Likelihood Estimates of the Proportion of Patients Cured by Cancer Therapy

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