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

Odds Ratio01:09

Odds Ratio

1.3K
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...
1.3K
Hazard Ratio01:12

Hazard Ratio

469
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
469
Relative Risk01:12

Relative Risk

1.6K
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...
1.6K
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

3.8K
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...
3.8K
Probability Laws01:49

Probability Laws

43.7K
Overview
43.7K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

6.4K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
6.4K

You might also read

Related Articles

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

Sort by
Same author

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

Statistical methods in medical research·2026
Same author

Integrated proteomic and metabolomic analyses implicate redox-metabolic pathways in PTSD-associated multisystem disease and accelerated aging.

Nature communications·2026
Same author

An ensemble approach to tensor learning.

Statistical methods in medical research·2026
Same author

Reduced Gray-White Matter Contrast in Chronic Posttraumatic Stress Disorder in World Trade Center Responders.

Biological psychiatry. Cognitive neuroscience and neuroimaging·2025
Same author

Lung Cancer Incidence After September 11, 2001, Among World Trade Center Responders.

JAMA network open·2025
Same author

Polygenic Risk and Exposure Severity Predict Trajectories of PTSD: A Prospective Cohort Study.

Molecular psychiatry·2025

Related Experiment Video

Updated: Dec 20, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.8K

Transformation based on likelihood ratio.

Jianping Yang1, Pei-Fen Kuan2, Jialiang Li3,4,5

  • 1Department of Mathematical Sciences, School of Science, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, China.

Statistical Methods in Medical Research
|May 27, 2020
PubMed
Summary

This study addresses a recent letter concerning likelihood ratio transformations. We provide a response clarifying the statistical methodology and its implications.

Keywords:
Diagnostic medicinearea under ROC curveclassification accuracylikelihood ratio transformationreceiver operating characteristic curve

More Related Videos

A Tactile Automated Passive-Finger Stimulator TAPS
19:44

A Tactile Automated Passive-Finger Stimulator TAPS

Published on: June 3, 2009

14.1K
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

2.4K

Related Experiment Videos

Last Updated: Dec 20, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.8K
A Tactile Automated Passive-Finger Stimulator TAPS
19:44

A Tactile Automated Passive-Finger Stimulator TAPS

Published on: June 3, 2009

14.1K
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

2.4K

Area of Science:

  • Statistics
  • Statistical Methodology

Background:

  • A recent letter discussed transformations based on likelihood ratios.
  • This letter prompted a need for clarification and further discussion within the statistical community.

Purpose of the Study:

  • To respond to a recent letter published in this journal.
  • To clarify and elaborate on the statistical transformation methods based on the likelihood ratio.

Main Methods:

  • The response involves a detailed examination of the statistical principles.
  • Analysis of the likelihood ratio transformation as presented in the prior letter.

Main Results:

  • The response offers a refined perspective on the likelihood ratio transformation.
  • Key statistical considerations are highlighted to ensure accurate interpretation.

Conclusions:

  • The discussion contributes to a deeper understanding of likelihood ratio transformations.
  • This response aims to foster accurate application of statistical methods in research.