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

Components of variance: a miscellany

D Cox1

  • 1Nuffield College, Oxford, UK. david.cox@nuf.ox.ac.uk

Statistical Methods in Medical Research
|April 9, 1998
PubMed
Summary
This summary is machine-generated.

This review examines general issues related to variance components. It covers definitions, statistical inference, model fit, and methods for analyzing unbalanced data.

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

Enhancing the Performance of a Blood-Based Diagnostic Screening Tool for Dysferlinopathy: Optimising an Immunoassay Across Continents.

Neuropathology and applied neurobiology·2026
Same author

Corrigendum to: "Pilot study of on-treatment platelet reactivity at low shear stress and platelet activation status on aspirin or clopidogrel monotherapy in patients with TIA or ischaemic stroke" [JNS 2025 Vol 475, 123540].

Journal of the neurological sciences·2025
Same author

Pilot study of on-treatment platelet reactivity at low shear stress and platelet activation status on aspirin or clopidogrel monotherapy in patients with TIA or ischaemic stroke.

Journal of the neurological sciences·2025
Same author

Assessment of on-treatment platelet reactivity at high and low shear stress and platelet activation status after the addition of dipyridamole to aspirin in the early and late phases after TIA and ischaemic stroke.

Journal of the neurological sciences·2022
Same author

[Impact of NGS results on patient outcome with a multiform glioblastoma].

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique·2022
Same author

Relationship between 'on-treatment platelet reactivity', shear stress, and micro-embolic signals in asymptomatic and symptomatic carotid stenosis.

Journal of neurology·2019
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

Area of Science:

  • Statistics
  • Statistical Modeling

Background:

  • Variance components are fundamental in statistical analysis.
  • Understanding their properties is crucial for accurate data interpretation.

Purpose of the Study:

  • To review general issues concerning variance components.
  • To discuss definitions, inference, goodness of fit, and methods for unbalanced data.

Main Methods:

  • Literature review of statistical concepts.
  • Discussion of theoretical frameworks for variance component analysis.

Main Results:

  • Clarification of definitional aspects of variance components.
  • Overview of formal inference within normal-theory contexts.
  • Consideration of goodness-of-fit diagnostics.

Related Experiment Videos

  • Introduction to methods for handling unbalanced data.

    • Conclusions:

    • A comprehensive understanding of variance components requires addressing definitional clarity and inference.
    • Effective methods exist for analyzing unbalanced data, enhancing statistical applicability.