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Photographic Capture-Recapture for Free-Roaming Dog Population Estimation: Is It Possible to Optimize the Dog Photo-Identification?

Author

Listed:
  • Beibei Guo

    (Department of Experimental Statistics, Louisiana State University, USA)

  • Rui Zhang

    (Department of Physics & Astronomy, Louisiana State University, USA)

Abstract

Recent success of immunotherapy and other targeted therapies in cancer treatment has signaled the advent of precision medicine. Unlike conventional trial designs that aim to find an optimal treatment ignoring inter-patient heterogeneity, clinical trial designs for precision medicine must take into account patients’ variability in genes, environments, and lifestyle. This article provides a review of recent research development of clinical trial designs toward this trend.

Suggested Citation

  • Beibei Guo & Rui Zhang, 2018. "Photographic Capture-Recapture for Free-Roaming Dog Population Estimation: Is It Possible to Optimize the Dog Photo-Identification?," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 5(3), pages 88-90, February.
  • Handle: RePEc:adp:jbboaj:v:5:y:2018:i:3:p:88-90
    DOI: 10.19080/BBOAJ.2018.05.555665
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    References listed on IDEAS

    as
    1. John O'Quigley & Xavier Paoletti, 2003. "Continual Reassessment Method for Ordered Groups," Biometrics, The International Biometric Society, vol. 59(2), pages 430-440, June.
    2. Beibei Guo & Ying Yuan, 2017. "Bayesian Phase I/II Biomarker-Based Dose Finding for Precision Medicine With Molecularly Targeted Agents," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 508-520, April.
    3. Nicholas J. Schork, 2015. "Personalized medicine: Time for one-person trials," Nature, Nature, vol. 520(7549), pages 609-611, April.
    4. Peter F. Thall & Hoang Q. Nguyen & Elihu H. Estey, 2008. "Patient-Specific Dose Finding Based on Bivariate Outcomes and Covariates," Biometrics, The International Biometric Society, vol. 64(4), pages 1126-1136, December.
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