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

Ross Maller; Sidney Resnick; Soudabeh Shemehsavar

doi:10.1002/cjs.11771

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

Journal article

Open access

Peer reviewed

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

Ross Maller, Sidney Resnick and Soudabeh Shemehsavar

Canadian journal of statistics, Early View

2023

DOI: https://doi.org/10.1002/cjs.11771

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Abstract

Mathematics

Physical Sciences

Science & Technology

Statistics & Probability

The 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.

Details

Title: Finite sample and asymptotic distributions of a statistic for sufficient follow-up in cure models
Authors/Creators: Ross Maller - Supreme Council Of Health
Sidney Resnick - Cornell University
Soudabeh Shemehsavar - University of Tehran
Publication Details: Canadian journal of statistics, Early View
Publisher: Wiley Periodicals LLC on behalf of Statistical Society of Canada / Société statistique du Canada.
Number of pages: 21
Identifiers: 991005602259607891
Murdoch Affiliation: College of Science, Technology, Engineering and Mathematics
Language: English
Resource Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Citation topics: 9 Mathematics; 9.92 Statistical Methods; 9.92.220 Robust Estimation
Web Of Science research areas: Statistics & Probability
ESI research areas: Mathematics