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Goodness-of-fit testing in the presence of cured data: IPCW approach

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  • Marija Cuparić

    (University of Belgrade)

  • Bojana Milošević

    (University of Belgrade)

Abstract

Here we revisit a goodness-of-fit testing problem for randomly right-censored data in the presence of cured subjects, i.e. the population consists of two parts: the cured or non-susceptible group, who will never experience the event of interest versus those who will undergo the event of interest when followed up sufficiently long. We consider the modifications of proposed characterization-based goodness-of-fit tests for the exponential distribution constructed via the inverse probability of censoring weighted U- or V-approach. We present their asymptotic properties and extend our discussion to encompass suitable generalizations applicable to a variety of tests formulated using the same methodology. A comparative power study of these proposed tests against a recent CvM-based competitor and the modifications of the most prominent competitors identified in prior studies that did not consider the presence of cured subjects, demonstrates good finite sample performance. Novel tests are illustrated on a real dataset related to leukemia relapse.

Suggested Citation

  • Marija Cuparić & Bojana Milošević, 2025. "Goodness-of-fit testing in the presence of cured data: IPCW approach," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 31(2), pages 233-252, April.
    • Handle: RePEc:spr:lifeda:v:31:y:2025:i:2:d:10.1007_s10985-025-09646-1
    DOI: 10.1007/s10985-025-09646-1
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    References listed on IDEAS

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    1. E. Bothma & J. S. Allison & I. J. H. Visagie, 2022. "New classes of tests for the Weibull distribution using Stein’s method in the presence of random right censoring," Computational Statistics, Springer, vol. 37(4), pages 1751-1770, September.
    2. Federico Felizzi & Noman Paracha & Johannes Pöhlmann & Joshua Ray, 2021. "Mixture Cure Models in Oncology: A Tutorial and Practical Guidance," PharmacoEconomics - Open, Springer, vol. 5(2), pages 143-155, June.
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    4. Katarina Halaj & Bojana Milošević & Marko Obradović & M. Dolores Jiménez-Gamero, 2024. "Correlation-type goodness-of-fit tests based on independence characterizations," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(1), pages 185-207, March.
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    10. Marija Cuparić & Bojana Milošević, 2022. "New characterization-based exponentiality tests for randomly censored data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 461-487, June.
    11. Sudheesh K. Kattumannil & P. Anisha, 2019. "A simple non-parametric test for decreasing mean time to failure," Statistical Papers, Springer, vol. 60(1), pages 73-87, February.
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