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Efficient Estimation of Semiparametric Transformation Model with Interval-Censored Data in Two-Phase Cohort Studies

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Abstract

Interval sampling and two-phase sampling have both been advocated for studying rare failure outcomes. With few exceptions focusing on specific designs such as the case-cohort design, they are often studied separately in the statistical literature and require different estimation procedures. We consider efficient estimation of interval-censored data collected in a two-phase sampling design using a localized nonparametric likelihood. An expectation maximization algorithm is proposed by exploiting multiple layers of data augmentation that handle transformation function, interval-censoring, and two-phase sampling structure simultaneously. We study the asymptotic properties of the estimators and conduct inference using profile likelihood. We illustrate the performance of the proposed estimator by simulations and an HIV vaccine trial.

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Acknowledgements

The authors thank Drs. Peter Gilbert and Yunda Huang, the HIV Vaccine Trials Network, and Merck for providing the Step 502/Merck 023+HVTN 504 data, which was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under the U.S. Public Health Service Grant AI068635 (Statistical and Data Management Center for the HIV Vaccine Trials Network). The content is solely the responsibility of the authors and does 345 not necessarily represent the official views of the National Institutes of Health. This work was supported by the U.S. National Institutes of Health Grants R01HL122212 and R37AI029168.

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Authors and Affiliations

  1. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA, 98109, USA

    Fei Gao

  2. Department of Biostatistics, University of Washington, 1705 NE Pacific St, Seattle, WA, 98195, USA

    Kwun Chuen Gary Chan

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  1. Fei Gao
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Correspondence to Fei Gao.

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Gao, F., Chan, K.C.G. Efficient Estimation of Semiparametric Transformation Model with Interval-Censored Data in Two-Phase Cohort Studies. Stat Biosci 16, 203–220 (2024). https://doi.org/10.1007/s12561-023-09392-8

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  • DOI: https://doi.org/10.1007/s12561-023-09392-8

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