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

Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

7.4K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
7.4K
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

6.5K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
6.5K
Multiple Comparison Tests01:13

Multiple Comparison Tests

4.0K
Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
4.0K
High-Performance Liquid Chromatography: Types of Detectors01:15

High-Performance Liquid Chromatography: Types of Detectors

964
The role of the detectors in High-Performance Liquid Chromatography (HPLC) is to analyze the solutes as they exit from the chromatographic column. The detector recognizes the solute's property and generates corresponding electrical signals, which are converted into a readable graph of the detector's response versus elution time called a chromatogram at the computer. There are several types of HPLC detectors, each with its own advantages and limitations, depending on the analyte...
964
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

811
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
811
Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

352
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...
352

You might also read

Related Articles

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

Sort by
Same author

Delta plots for conflict tasks: An activation-suppression race model.

Psychonomic bulletin & review·2021
Same author

The Müller-Lyer line-length task interpreted as a conflict paradigm: A chronometric study and a diffusion account.

Attention, perception & psychophysics·2020
Same author

Categorizing digits and the mental number line.

Attention, perception & psychophysics·2019
Same author

Aging effects on symbolic number comparison: No deceleration of numerical information retrieval but more conservative decision-making.

Psychology and aging·2018
Same author

The number-weight illusion.

Psychonomic bulletin & review·2018
Same author

Implications of individual differences in on-average null effects.

Journal of experimental psychology. General·2017
Same journal

Low prevalence targets are primarily missed due to mind wandering.

Attention, perception & psychophysics·2026
Same journal

An introduction to the special issue celebrating Mary A. Peterson.

Attention, perception & psychophysics·2026
Same journal

Properties of the threshold stimulus exposure duration (TSED) measure of visual search efficiency.

Attention, perception & psychophysics·2026
Same journal

Auditory selective attention in depth: Investigating directional dependency across front, lateral, and rear spaces.

Attention, perception & psychophysics·2026
Same journal

Dissociations between stereoacuity and visual acuity with binocular night vision goggles.

Attention, perception & psychophysics·2026
Same journal

Reward-based prioritization and perceptual feature effects on attentional flexibility in working memory.

Attention, perception & psychophysics·2026
See all related articles

Related Experiment Video

Updated: Oct 17, 2025

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.9K

The conditional approach to evaluating detection performance.

Wolf Schwarz1

  • 1Department of Psychology, University of Potsdam, P.O. Box 60 15 53, D - 14415, Potsdam, Germany. wschwarz@uni-potsdam.de.

Attention, Perception & Psychophysics
|October 9, 2021
PubMed
Summary
This summary is machine-generated.

A new conditional statistical approach precisely estimates observer sensitivity in Yes/No signal-detection studies. This method provides exact confidence intervals for the odds ratio, improving upon traditional unconditional methods.

Keywords:
Conditional inferenceFisher’s exact testLikelihood-based confidence intervalsNoncentral hypergeometric distributionOdds ratioSignal detection

More Related Videos

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.1K
Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses
14:05

Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses

Published on: January 23, 2017

29.3K

Related Experiment Videos

Last Updated: Oct 17, 2025

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.9K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.1K
Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses
14:05

Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses

Published on: January 23, 2017

29.3K

Area of Science:

  • Decision analysis
  • Psychometrics
  • Statistical inference

Background:

  • Single-point Yes/No signal-detection studies often focus on observer sensitivity, using metrics like the discrimination index d'.
  • Traditional methods may not fully account for the conditional nature of inferences drawn from observed responses.
  • Existing approaches like Fisher's exact test and Rasch models highlight the value of conditional inference in related fields.

Purpose of the Study:

  • To introduce and detail a conditional statistical approach for Yes/No signal-detection studies.
  • To demonstrate how this framework enables exact inference and estimation of sensitivity.
  • To compare the conditional approach with classical unconditional methods.

Main Methods:

  • Utilizing the noncentral hypergeometric sampling distribution for exact inference.
  • Applying conditional maximum likelihood estimation for sensitivity.
  • Deriving exact confidence intervals for the log odds ratio.
  • Relating the conditional approach to logistic detection models.

Main Results:

  • The conditional approach provides exact inference for any sample size by eliminating nuisance parameters.
  • Conditional maximum likelihood estimates of sensitivity are obtained.
  • Exact confidence intervals for the underlying log odds ratio are generated.
  • Comparison with unconditional approaches regarding statistical power is discussed.

Conclusions:

  • The conditional framework offers a statistically rigorous method for analyzing Yes/No signal-detection data.
  • It provides exact confidence intervals, enhancing the reliability of sensitivity estimates.
  • This approach offers advantages in specific scenarios, warranting consideration in applied research.