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Related Experiment Video

Updated: Aug 31, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Confidence bands in survival analysis.

Michael C Sachs1, Adam Brand2, Erin E Gabriel3

  • 1Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark. michael.sachs@sund.ku.dk.

British Journal of Cancer
|August 19, 2022
PubMed
Summary
This summary is machine-generated.

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Simultaneous confidence bands provide accurate uncertainty estimates for survival curves, unlike standard methods. New software is needed for easier computation of these essential statistical tools.

Area of Science:

  • Statistics
  • Biostatistics
  • Survival Analysis

Background:

  • Estimating uncertainty for statistical quantities is crucial for inference.
  • Survival curves, as functions over time, require simultaneous confidence bands that account for point correlations.
  • Standard software often provides confidence intervals at discrete time points, not true simultaneous bands.

Purpose of the Study:

  • To evaluate the properties of different types of confidence bands for survival curves.
  • To compare standard confidence bands with simultaneous confidence bands.
  • To provide practical guidance and code for constructing simultaneous confidence bands.

Main Methods:

  • Comparison of joint/simultaneous coverage properties of different confidence band types.

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  • Investigation of likelihood ratio-based simultaneous confidence bands.
  • Illustration using a colon cancer study dataset.

    • Main Results:

    • Standard confidence bands lack desirable joint/simultaneous coverage properties.
    • Likelihood ratio-based simultaneous confidence bands exhibit the most favorable properties.
    • Code is provided for constructing alternative simultaneous bands using existing statistical software.

    Conclusions:

    • Simultaneous confidence bands are superior to standard methods for survival curve uncertainty estimation.
    • There is a significant need for user-friendly statistical software to implement likelihood-based simultaneous confidence bands.
    • Further development of statistical software is required to facilitate the application of advanced survival analysis techniques.