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

Measuring agreement in method comparison studies.

J M Bland1, D G Altman

  • 1Department of Public Health Sciences, St George's Hospital Medical School, London, UK.

Statistical Methods in Medical Research
|September 29, 1999
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

CONSORT 2010 statement: extension checklist for reporting within person randomised trials.

The British journal of dermatology·2019
Same author

'Allocation concealment': the evolution and adoption of a methodological term.

Journal of the Royal Society of Medicine·2018
Same author

[Better Reporting of Interventions: Template for Intervention Description and Replication (TIDieR) Checklist and Guide].

Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany))·2018
Same author

GRIPP2 reporting checklists: tools to improve reporting of patient and public involvement in research.

Research involvement and engagement·2017
Same author

GRIPP2 reporting checklists: tools to improve reporting of patient and public involvement in research.

BMJ (Clinical research ed.)·2017
Same author

Quality control of ultrasound for fetal biometry: results from the INTERGROWTH-21<sup>st</sup> Project.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology·2017
Same journal

A joint model for a longitudinal outcome and a progressive multistate model under a mixed observation scheme.

Statistical methods in medical research·2026
Same journal

Efficient semi-supervised estimation of optimal individualized treatment regimes with survival outcome.

Statistical methods in medical research·2026
Same journal

Asymptotic online FWER control for dependent test statistics.

Statistical methods in medical research·2026
Same journal

Regression analysis of misclassified current status data with potentially unknown test accuracy.

Statistical methods in medical research·2026
Same journal

Bayesian multivariate linear mixed-effects models with varied association structures.

Statistical methods in medical research·2026
Same journal

Inference about the ratio of age-standardized rates between two overlapping populations.

Statistical methods in medical research·2026
See all related articles

Quantifying agreement between clinical measurement methods is crucial. This study introduces methods to estimate limits of agreement, analyze data with varying magnitudes, and handle repeated measurements for robust clinical assessment.

Area of Science:

  • Biostatistics
  • Clinical Measurement
  • Medical Device Evaluation

Background:

  • Clinical measurement methods require rigorous agreement assessment.
  • Traditional methods for quantifying agreement have limitations.
  • Understanding measurement error is vital for clinical decision-making.

Purpose of the Study:

  • To quantify agreement between two clinical measurement methods.
  • To extend agreement analysis to complex data structures and relationships.
  • To provide graphical and statistical tools for assumption investigation.

Main Methods:

  • Calculation of 95% limits of agreement using mean difference and standard deviation.
  • Application of graphical methods for assumption checking and confidence interval estimation.

Related Experiment Videos

  • Development of regression and logarithmic transformation approaches for magnitude-dependent differences.
  • Extension to repeated measurements, including unequal replicates and paired data with changing values.
  • Introduction of a nonparametric approach for method comparison.

    • Main Results:

    • Established a framework for quantifying agreement using limits of agreement.
    • Demonstrated methods to address relationships between measurement differences and magnitude.
    • Provided solutions for analyzing repeated and paired measurement data.
    • Introduced graphical tools for visualizing agreement and assessing assumptions.

    Conclusions:

    • The proposed methods offer a comprehensive approach to assessing agreement between clinical measurement techniques.
    • The techniques are adaptable to various data complexities, including repeated measures and magnitude-dependent errors.
    • Graphical and statistical tools enhance the reliability and interpretability of agreement analyses in clinical research.