Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Tutorial: using confidence curves in medical research.

Ralf Bender1, Gabriele Berg, Hajo Zeeb

  • 1Institute for Quality and Efficiency in Health Care, Cologne, Germany. Ralf.Bender@iqwig.de

Biometrical Journal. Biometrische Zeitschrift
|January 5, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Shifts in the Rhizosphere Bacterial Community and Improved Essential Oil Yield and Quality in Chamomilla recutita L. Plant Through Cyanobacterial Inoculation.

Microbial ecology·2026
Same author

From "synthetic" to defined microbial communities for clearer terminology.

Nature communications·2026
Same author

Diversity and selected functional traits of microbiota associated with traditional dried plant foods from South African informal markets.

FEMS microbes·2026
Same author

Microbial diversity creates a global firewall against pathogens in soil.

Cell host & microbe·2026
Same author

Nano-selenium coordinates plant-microbiome redox for sustainable crops.

Trends in plant science·2026
Same author

Multiple origins of the apple seed microbiome: disentangling sexual and asexual transmission pathways.

Environmental microbiome·2026
Same journal

When to Adjust for Multiple Testing: A Unifying Guiding Principle.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Ensuring Quality in Preclinical Research: The Importance of Being Human.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Addressing Cluster-Level Treatment Effect Heterogeneity in Sample Size Determination for Hierarchical 2 × 2 Factorial Designs.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

A Multiple Imputation Approach to Distinguish Curative From Life-Prolonging Effects in the Presence of Missing Covariates.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Tests for Categorical Data Beyond Pearson: A Distance Covariance and Energy Distance Approach.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Nonparametric Estimation of the Patient-Weighted While-Alive Estimand.

Biometrical journal. Biometrische Zeitschrift·2026
See all related articles

Confidence curves offer a visual way to show uncertainty in research findings across all confidence levels. They provide a valuable alternative to traditional confidence intervals, enhancing the interpretation of statistical inference.

Area of Science:

  • Biostatistics
  • Medical Research Methodology
  • Statistical Inference

Background:

  • Confidence intervals are standard for quantifying uncertainty in estimated effects.
  • The conventional fixed 95% confidence level is typically used.
  • Confidence curves, though proposed for decades, are underutilized in medical research.

Purpose of the Study:

  • To introduce confidence curves as a graphical tool for visualizing uncertainty.
  • To review the history and interpretation of confidence curves.
  • To highlight the impact of one-sided versus two-sided statistical inference on confidence curves.

Main Methods:

  • Graphical illustration of confidence intervals across varying confidence levels (0-100%).
  • Analysis of the influence of one-sided and two-sided statistical inference on confidence curve plotting.

Related Experiment Videos

  • Demonstration of appropriate interpretation for both one-sided and two-sided confidence curves.

    • Main Results:

    • Confidence curves provide a comprehensive view of uncertainty beyond a single confidence level.
    • The choice between one-sided and two-sided inference significantly affects confidence curve construction and interpretation.
    • Confidence curves can be effectively used to complement conventional methods for presenting study results.

    Conclusions:

    • Confidence curves are valuable graphical tools for presenting statistical uncertainty.
    • Greater emphasis should be placed on selecting between one-sided and two-sided inference in medical research.
    • One- and two-sided confidence curves enhance the understanding and reporting of study findings.