Constructing time‐invariant dynamic surveillance rules for optimal monitoring schedules
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DOI: 10.1111/biom.13911
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- Lixing Zhu & Liugen Xue, 2006. "Empirical likelihood confidence regions in a partially linear single‐index model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(3), pages 549-570, June.
- Tracey L. Marsh & Holly Janes & Margaret S. Pepe, 2020. "Statistical inference for net benefit measures in biomarker validation studies," Biometrics, The International Biometric Society, vol. 76(3), pages 843-852, September.
- Cain Lauren E. & Robins James M. & Lanoy Emilie & Logan Roger & Costagliola Dominique & Hernán Miguel A., 2010. "When to Start Treatment? A Systematic Approach to the Comparison of Dynamic Regimes Using Observational Data," The International Journal of Biostatistics, De Gruyter, vol. 6(2), pages 1-26, April.
- Bibhas Chakraborty & Palash Ghosh & Erica E. M. Moodie & A. John Rush, 2016. "Estimating optimal shared-parameter dynamic regimens with application to a multistage depression clinical trial," Biometrics, The International Biometric Society, vol. 72(3), pages 865-876, September.
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