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Nonparametric tests for multistate processes with clustered data

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Abstract

In this work, we propose nonparametric two-sample tests for population-averaged transition and state occupation probabilities for continuous-time and finite state space processes with clustered, right-censored, and/or left-truncated data. We consider settings where the two groups under comparison are independent or dependent, with or without complete cluster structure. The proposed tests do not impose assumptions regarding the structure of the within-cluster dependence and are applicable to settings with informative cluster size and/or non-Markov processes. The asymptotic properties of the tests are rigorously established using empirical process theory. Simulation studies show that the proposed tests work well even with a small number of clusters, and that they can be substantially more powerful compared to the only, to the best of our knowledge, previously proposed nonparametric test for this problem. The tests are illustrated using data from a multicenter randomized controlled trial on metastatic squamous-cell carcinoma of the head and neck.

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Acknowledgements

We thank the Associate Editor and the two anonymous reviewers for their insightful comments which helped us to significantly improve this manuscript. This article is based on research using data obtained from www.projectdatasphere.org, which is maintained by Project Data Sphere. Neither Project Data Sphere nor the owner(s) of any information from the web site have contributed to, approved, or are in any way responsible for the contents of this article. Bakoyannis acknowledges funding support from Grants R21AI145662 and R01AI140854 from the National Institutes of Health. Bandyopadhyay acknowledges funding support from Grant P30CA016059 from the National Institutes of Health.

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Authors and Affiliations

  1. Department of Biostatistics and Health Data Science, Indiana University, 410 West 10th Street, Suite 3000, Indianapolis, IN, 46202, USA

    Giorgos Bakoyannis

  2. Department of Biostatistics, Virginia Commonwealth University, 830 East Main Street, Richmond, VA, 23219, USA

    Dipankar Bandyopadhyay

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  1. Giorgos Bakoyannis
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  2. Dipankar Bandyopadhyay
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Correspondence to Giorgos Bakoyannis.

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Bakoyannis, G., Bandyopadhyay, D. Nonparametric tests for multistate processes with clustered data. Ann Inst Stat Math 74, 837–867 (2022). https://doi.org/10.1007/s10463-021-00819-x

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  • DOI: https://doi.org/10.1007/s10463-021-00819-x

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