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Nonparametric Survival Analysis

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Principles and Practice of Clinical Trials

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Abstract

Survival or time-to-event data are ubiquitous in clinical trials research. The presence of censoring requires specialized methods for the analysis of this type of data. This chapter describes the methods for nonparametric analyses of survival data, including estimation of the key survival quantities of interest and hypothesis testing.

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Author information

Authors and Affiliations

  1. Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA

    Yuliya Lokhnygina

Authors
  1. Yuliya Lokhnygina
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Corresponding author

Correspondence to Yuliya Lokhnygina .

Editor information

Editors and Affiliations

  1. Department of Surgery, Division of Surgical Oncology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Steven Piantadosi

  2. Department of Epidemiology, School of Public Health, Johns Hopkins University, Baltimore, MD, USA

    Curtis L. Meinert

Section Editor information

  1. Department of Biostatistics and Bioinformatics, Basic Science Division, Duke University School of Medicine, Durham, NC, USA

    Stephen L. George PhD

  2. The Johns Hopkins Center for Clinical Trials and Evidence Synthesis, Johns Hopkins School of Public Health, Baltimore, MA, USA

    Curtis L. Meinert

  3. Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Steven Piantadosi

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Lokhnygina, Y. (2022). Nonparametric Survival Analysis. In: Piantadosi, S., Meinert, C.L. (eds) Principles and Practice of Clinical Trials. Springer, Cham. https://doi.org/10.1007/978-3-319-52636-2_119

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