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 Concept Videos

Variability: Analysis01:11

Variability: Analysis

Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...

You might also read

Related Articles

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

Sort by
Same author

The impact of an educational podcast on emotional wellbeing and attitudes towards Charles Bonnet syndrome hallucinations.

Therapeutic advances in ophthalmology·2026
Same author

Location of visual field defects and their impact on vision-related quality of life in glaucoma: A systematic review.

Optometry and vision science : official publication of the American Academy of Optometry·2026
Same author

Genetic Risk Factors and Clinical Implications of Glaucoma in the Saudi Population: A Review.

International journal of molecular sciences·2026
Same author

Longitudinal Visual Field and Quality-of-Life Change in the Treatment for Advanced Glaucoma Study.

Ophthalmology·2026
Same author

Archetypes of Binocular Visual Field Loss and Their Impact on Vision-Related Quality of Life in Glaucoma Patients.

Investigative ophthalmology & visual science·2026
Same author

Assessing the resilience of portable vision tests to an uncontrolled home environment.

PeerJ·2026

Related Experiment Video

Updated: May 19, 2026

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity
06:46

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

The relationship between variability and sensitivity in large-scale longitudinal visual field data.

Richard A Russell1, David P Crabb, Rizwan Malik

  • 1Department of Optometry and Visual Science, City University London, UK.

Investigative Ophthalmology & Visual Science
|August 11, 2012
PubMed
Summary
This summary is machine-generated.

Visual field damage variability increases as sensitivity decreases. This study quantifies this using statistical methods on large patient datasets, aiding glaucoma progression detection.

More Related Videos

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients
07:06

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients

Published on: March 29, 2022

Related Experiment Videos

Last Updated: May 19, 2026

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity
06:46

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients
07:06

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients

Published on: March 29, 2022

Area of Science:

  • Ophthalmology
  • Statistical analysis
  • Glaucoma research

Background:

  • Standard automated perimetry (SAP) pointwise sensitivity data is used to evaluate progressive visual field (VF) damage.
  • Frequency-of-seeing and test-retest studies show high variability in SAP measurements, particularly in damaged areas.
  • Existing methods for characterizing VF variability are limited by small sample sizes.

Purpose of the Study:

  • To characterize visual field (VF) variability based on sensitivity levels.
  • To develop a statistical method for quantifying heteroscedasticity in VF sensitivity data.
  • To provide a robust approach for distinguishing real VF progression from measurement variability.

Main Methods:

  • Retrospective analysis of 14,887 Humphrey 24-2 SITA Standard VFs from 2736 patients.
  • Pointwise linear regression of sensitivity over time for each patient's VF series.
  • Pooling of regression residuals based on observed and fitted sensitivities to quantify variability.

Main Results:

  • Inferred variability as a function of fitted sensitivity aligned with previous estimates.
  • Variability was confirmed to increase rapidly as observed sensitivity decreased.
  • The study utilized a large dataset, providing robust statistical inference.

Conclusions:

  • A novel statistical approach effectively characterizes visual field (VF) variability by sensitivity level.
  • This method, based on thousands of clinic patients, offers greater reliability than small test-retest studies.
  • Findings will enhance glaucoma progression detection models by differentiating true progression from measurement noise.