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

Ordinal Level of Measurement00:55

Ordinal Level of Measurement

22.4K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
22.4K
Interval Level of Measurement00:55

Interval Level of Measurement

14.1K
For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...
14.1K
Ranks01:02

Ranks

202
Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
202
Nominal Level of Measurement00:56

Nominal Level of Measurement

27.1K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal...
27.1K
Ratio Level of Measurement00:54

Ratio Level of Measurement

17.1K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated....
17.1K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

85
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...
85

You might also read

Related Articles

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

Sort by
Same author

CDC20 promotes prostate cancer progression via modulating c-MYC and PI3K-AKT signaling.

iScience·2026
Same author

Exploring distributed leadership and proactive change behavior in nursing: the roles of psychological safety and inclusive climate.

Scientific reports·2026
Same author

Galectin-3 Regulates Smooth Muscle Contraction and Blood Pressure by Modulating Ca<sub>V</sub>1.2 Channel Function.

Circulation·2026
Same author

Automatic identification of anatomical landmarks in three-dimensional computed tomography/cone-beam computed tomography: a scoping review.

Frontiers in dental medicine·2026
Same author

MicroRNA-563 as a potential biomarker in triple-negative breast cancer: impeding tumor progression by targeting ITGAV and epithelial-mesenchymal transition.

World journal of surgical oncology·2026
Same author

Cross-lagged panel model among metacognitions about gambling, emotion regulation, and gambling disorder: A two-wave longitudinal study.

Addictive behaviors·2026
Same journal

Correction.

Journal of biopharmaceutical statistics·2026
Same journal

Leveraging external controls in clinical trials: estimands, estimation, assumptions.

Journal of biopharmaceutical statistics·2026
Same journal

Special issue of nonclinical statistics in regulatory applications guest editors' notes.

Journal of biopharmaceutical statistics·2026
Same journal

Comparison of flexible parametric modeling and nonparametric methods to estimate restricted mean survival time: A simulation study.

Journal of biopharmaceutical statistics·2026
Same journal

Simulated treatment comparisons with jackknife pseudo values for estimating population-adjusted marginal treatment effects.

Journal of biopharmaceutical statistics·2026
Same journal

Sample sizes for randomized controlled trials utilizing Bayesian response adaptive randomization for continuous outcomes.

Journal of biopharmaceutical statistics·2026
See all related articles

Related Experiment Video

Updated: May 10, 2025

A Two-interval Forced-choice Task for Multisensory Comparisons
07:13

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

10.8K

Comparison of continuous, binary, and ordinal endpoints.

Jing Zhai1, Fraser Smith1, Guoxing Soon1

  • 1Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA.

Journal of Biopharmaceutical Statistics
|April 26, 2025
PubMed
Summary
This summary is machine-generated.

Clinical trials can improve study power by using ordinal endpoints. This approach, using multiple cut points instead of a single binary threshold, offers advantages when designing clinical trials.

Keywords:
Binary endpointcontinuous endpointordinal endpointsimulation studiesstatistical power

More Related Videos

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

2.9K
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.3K

Related Experiment Videos

Last Updated: May 10, 2025

A Two-interval Forced-choice Task for Multisensory Comparisons
07:13

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

10.8K
RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

2.9K
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.3K

Area of Science:

  • Clinical trial design
  • Biostatistics
  • Medical research methodology

Background:

  • Selecting primary endpoints is a critical challenge in clinical trial design.
  • Common endpoints include binary, continuous, and time-to-event measures.
  • Binary endpoints, derived from continuous data thresholds, often lead to underpowered studies due to threshold uncertainty.

Purpose of the Study:

  • To propose and evaluate the use of ordinal endpoints as an alternative to traditional binary endpoints in clinical trials.
  • To assess the performance of continuous, binary, and ordinal endpoints through simulation and comparative analyses.
  • To demonstrate the potential advantages of ordinal endpoints in maintaining study power and managing uncertainty in clinical trial design.

Main Methods:

  • Extensive simulation studies were conducted to evaluate endpoint performance.
  • Comparative analysis of continuous, binary, and ordinal endpoints across multiple clinical trials.
  • Statistical modeling and risk distribution across multiple cut points for ordinal endpoints.

Main Results:

  • Ordinal endpoints can mitigate the risk associated with selecting a single threshold for binary endpoints.
  • Simulation studies indicate that ordinal endpoints can maintain study power even with unexpected results.
  • Comparative analyses across trials suggest advantages for ordinal endpoints in specific clinical scenarios.

Conclusions:

  • Ordinal endpoints offer a viable strategy to enhance statistical power in clinical trials.
  • The use of ordinal endpoints, defined by multiple cut points, can provide greater flexibility and robustness in endpoint selection.
  • Clinical and statistical considerations support the potential advantages of ordinal categorical endpoints as primary or secondary efficacy measures.