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

[Statistical approaches to evaluate agreement].

Josep Lluís Carrasco1, Lluís Jover

  • 1Bioestadística, Departamento de Salud Pública, Universitat de Barcelona, Spain.carrasco@medicina.ub.es

Medicina Clinica
|February 26, 2004
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

Clustering longitudinal data: comparison of model-based and distance-based approaches using simulated and real-world data in psychiatric research.

BMC medical research methodology·2026
Same author

Antagonistic SMAD2/3 control of TIMP-1, VEGF-A, and hypoxia signaling in myofibroblasts shapes histotype-specific angiogenesis in lung cancer.

Cell death & disease·2026
Same author

Predicting early clinical recovery in first-episode psychosis: development and external validation of a clinically interpretable multivariable model.

The British journal of psychiatry : the journal of mental science·2026
Same author

Differentiating Borderline from Malignant Ovarian-Adnexal Tumours: A Multimodal Predictive Approach Joining Clinical, Analytic, and MRI Parameters.

Cancers·2026
Same author

PET/CT Volumetric Parameters as Predictors of the Peritoneal Cancer Index in Advanced Ovarian Cancer Patients.

Diagnostics (Basel, Switzerland)·2025
Same author

Risk factors for glucocorticoid induced osteoporosis in young adults.

Frontiers in endocrinology·2025
Same journal

Treatment of phantom limb syndrome with ketamine.

Medicina clinica·2026
Same journal

Comment on "Ticagrelor versus clopidogrel in patients with chronic coronary syndrome undergoing percutaneous coronary intervention: A propensity score-matched analysis".

Medicina clinica·2026
Same journal

Limitations in the interpretation of thyroid function tests.

Medicina clinica·2026
Same journal

Cerebrotendinous xanthomatosis without neurological manifestations: An atypical form with normal cholestanol levels.

Medicina clinica·2026
Same journal

Dengue epidemic in Northern Peru (2024): analysis of 2,449 cases.

Medicina clinica·2026
Same journal

Transient first-degree atrioventricular block following acute vortioxetine overdose.

Medicina clinica·2026
See all related articles

Measurement error in health sciences can confound results. This study highlights issues with unreliable methods and suggests better ways to assess measurement agreement and error sources for accurate data.

Area of Science:

  • Health Sciences
  • Biostatistics
  • Medical Measurement

Background:

  • Reliability and agreement of measurement methods are critical in health sciences but often overlooked.
  • Measurement error can significantly impact study outcomes and lead to incorrect conclusions.
  • The switchability between measurements from disagreeing methods is a key concern.

Purpose of the Study:

  • To highlight the implications of using measurement methods with error.
  • To illustrate the confounding effects of measurement error with practical examples.
  • To propose and classify procedures for assessing agreement and identifying error sources.

Main Methods:

  • Procedures for assessing agreement and identifying error sources are presented.
  • Methods are categorized by data type (quantitative/qualitative) and assessment approach (aggregate/disaggregate).

Related Experiment Videos

  • Critique of commonly used agreement assessment methods like average comparison, correlation, and regression.

    • Main Results:

    • Measurement error can produce confounding effects in health science research.
    • Frequently used methods for assessing agreement (e.g., correlation coefficient, regression) are often insufficient.
    • Disaggregate analysis of error sources provides a more thorough assessment than aggregate measures.

    Conclusions:

    • Standard methods for assessing measurement agreement in health sciences are frequently inadequate.
    • Accurate assessment of measurement reliability and agreement is essential for valid research.
    • Newer, more detailed procedures are needed to properly evaluate measurement error and agreement.