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

Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

285
A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
285
Odds Ratio01:09

Odds Ratio

186
The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
186
The Mantel-Cox Log-Rank Test01:19

The Mantel-Cox Log-Rank Test

443
The Mantel-Cox log-rank test is a widely used statistical method for comparing the survival distributions of two groups. It tests whether a statistically significant difference exists in survival times between the groups without assuming a specific distribution for the survival data, making it a non-parametric test. This flexibility makes the log-rank test particularly valuable in medical research and other fields where the timing of an event, such as death or disease recurrence, is of...
443
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

3.4K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
3.4K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

228
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
228
Relative Risk01:12

Relative Risk

238
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
238

You might also read

Related Articles

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

Sort by
Same author

Optimal sizing of electric vehicle charging station considering charging scheduling strategy.

Scientific reports·2026
Same author

Asymptotic uncertainty of false discovery proportion.

Biometrics·2024
Same author

High-resolution electric power load data of an industrial park with multiple types of buildings in China.

Scientific data·2023
Same author

Prokineticin-2 Participates in Chronic Constriction Injury-Triggered Neuropathic Pain and Anxiety via Regulated by NF-κB in Nucleus Accumbens Shell in Rats.

Molecular neurobiology·2023
Same author

NIR-Activatable Heterostructured Nanoadjuvant CoP/NiCoP Executing Lactate Metabolism Interventions for Boosted Photocatalytic Hydrogen Therapy and Photoimmunotherapy.

Advanced materials (Deerfield Beach, Fla.)·2023
Same author

The Lin28b/Wnt5a axis drives pancreas cancer through crosstalk between cancer associated fibroblasts and tumor epithelium.

Nature communications·2023
Same journal

A Mixture of Distributed Lag Non-Linear Models to Account for Spatially Heterogeneous Exposure-Lag-Response Associations.

Statistics in medicine·2026
Same journal

Practical Considerations for Gaussian Process Modeling for Causal Inference in Quasi-Experimental Studies With Panel Data.

Statistics in medicine·2026
Same journal

Covariate Adjustment for Wilcoxon Two Sample Statistic and Test.

Statistics in medicine·2026
Same journal

Beyond Fixed Thresholds: Optimizing Summaries of Wearable Device Data via Piecewise Linearization of Quantile Functions.

Statistics in medicine·2026
Same journal

A Causal Framework for Evaluating the Total Effect of Strategies Aiming to Expand Screening and to Improve Outcomes.

Statistics in medicine·2026
Same journal

Causal Effects on Nonterminal Event Time With Application to Antibiotic Usage and Future Resistance.

Statistics in medicine·2026
See all related articles

Related Experiment Video

Updated: Jul 26, 2025

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.1K

Statistical inference for the two-sample problem under likelihood ratio ordering, with application to the ROC curve

Dingding Hu1, Meng Yuan1, Tao Yu2

  • 1Department of Statistics and Actuarial Sciences, University of Waterloo, Waterloo, Ontario, Canada.

Statistics in Medicine
|June 13, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a new statistical method using Bernstein polynomials and maximum empirical likelihood for Receiver Operating Characteristic (ROC) curve estimation. The method accurately models biomarker distributions, enhancing diagnostic accuracy in medical research.

Keywords:
Bernstein polynomialsROC curveYouden indexarea under the ROC curvelikelihood ratio ordering

More Related Videos

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
09:00

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Published on: August 16, 2024

829
Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
06:16

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

461

Related Experiment Videos

Last Updated: Jul 26, 2025

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.1K
Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
09:00

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

Published on: August 16, 2024

829
Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
06:16

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease

Published on: August 9, 2024

461

Area of Science:

  • Biostatistics
  • Medical Informatics
  • Statistical Modeling

Background:

  • Receiver Operating Characteristic (ROC) curves are vital statistical tools in medical research for evaluating diagnostic tests.
  • A common assumption in ROC analysis is that higher biomarker values indicate greater disease severity.
  • This assumption can be mathematically interpreted as a higher probability of disease with increased biomarker values.

Purpose of the Study:

  • To develop a novel statistical method for ROC curve estimation.
  • To model biomarker distributions using Bernstein polynomials and maximum empirical likelihood.
  • To provide a robust estimation of ROC curves and associated statistics.

Main Methods:

  • Proposed a Bernstein polynomial method to model biomarker distributions in diseased and healthy populations.
  • Employed the maximum empirical likelihood principle for distribution estimation.
  • Derived ROC curve estimates and summary statistics based on the modeled distributions.

Main Results:

  • The proposed method demonstrates theoretical asymptotic consistency.
  • Extensive numerical studies show competitive performance compared to existing methods.
  • The method's applicability is validated through a real-world data example.

Conclusions:

  • The Bernstein polynomial and maximum empirical likelihood approach offers a reliable method for ROC curve estimation.
  • This method enhances the statistical analysis of biomarkers in medical research.
  • The findings support the use of this technique for improved diagnostic accuracy assessment.