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

Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Errors In Hypothesis Tests01:14

Errors In Hypothesis Tests

When performing a hypothesis test, there are four possible outcomes depending on the actual truth (or falseness) of the null hypothesis and the decision to reject or not.
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Eyewitness Memory01:22

Eyewitness Memory

Eyewitness memory refers to the recollection of events by someone who has directly witnessed them, often serving as critical evidence in legal settings. This type of memory is commonly used in criminal cases where a witness describes details like a suspect's appearance, clothing, or behavior during a crime. However, despite its perceived reliability, eyewitness memory is prone to significant errors.
One such error is memory distortion, which occurs because human memory does not function like a...
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5% chance...
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

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...

You might also read

Related Articles

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

Sort by
Same author

From caller to suspect: Identifying behaviors that trigger suspicion in 911 calls.

Law and human behavior·2025
Same author

The psychological allure of Alford: Does wanting to appear innocent put innocents at risk?

Law and human behavior·2025
Same author

Police-induced confessions, 2.0: Risk factors and recommendations.

Law and human behavior·2025
Same author

Failing to express emotion on 911 calls triggers suspicion through violating expectations and moral typecasting.

Journal of personality and social psychology·2025
Same author

The "Partial Innocence" Effect: False Guilty Pleas to Partially Unethical Behaviors.

Personality & social psychology bulletin·2023
Same author

Perceptions of custody: Similarities and disparities among police, judges, social psychologists, and laypeople.

Law and human behavior·2021
Same journal

Viewing police body-worn camera video of use-of-force incidents: Does repeated or slow-motion viewing matter?

Law and human behavior·2026
Same journal

Psychopathy in the context of adversity: Understanding associations of early-life adversity and psychopathic symptoms in a sample of justice-involved youth.

Law and human behavior·2026
Same journal

Race and ethnicity in the courtroom workgroup: Can diversifying the court solve racial and ethnic disparities in case outcomes?

Law and human behavior·2026
Same journal

The justice motive: Retributive and restorative factors affect public evaluations of child protection.

Law and human behavior·2026
Same journal

A risk-need-responsivity (RNR)-informed systematic review of needs during the pretrial period.

Law and human behavior·2026
Same journal

When we do not care about what happens to "criminals": How character judgments influence indifference to incidental suffering in the criminal justice system.

Law and human behavior·2026
See all related articles

Related Experiment Video

Updated: May 23, 2026

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
09:49

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Published on: December 24, 2015

Harmless error analysis: How do judges respond to confession errors?

D Brian Wallace1, Saul M Kassin

  • 1Department of Psychology, John Jay College of Criminal Justice, City University of New York Graduate Center, New York, NY, USA. dwallace@jjay.cuny.edu

Law and Human Behavior
|April 5, 2012
PubMed
Summary
This summary is machine-generated.

Judges can identify coerced confessions but may still be influenced by them. Appellate judges can perform harmless error analysis, yet improper confessions impact conviction rates.

More Related Videos

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
07:36

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

Published on: May 3, 2016

Errors as a Means of Reducing Impulsive Food Choice
07:07

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

Related Experiment Videos

Last Updated: May 23, 2026

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
09:49

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

Published on: December 24, 2015

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
07:36

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

Published on: May 3, 2016

Errors as a Means of Reducing Impulsive Food Choice
07:07

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

Area of Science:

  • Psychology
  • Law
  • Cognitive Science

Background:

  • The U.S. Supreme Court's ruling in Arizona v. Fulminante (1991) permitted harmless error analysis for coerced confessions.
  • Understanding judicial decision-making in cases involving improperly admitted evidence is crucial for legal reform.

Purpose of the Study:

  • To investigate how judges evaluate coerced confessions and apply harmless error analysis.
  • To assess the impact of improperly admitted coerced confessions on judicial conviction rates.

Main Methods:

  • 132 judges from three states participated in the study.
  • Participants reviewed a murder case summary, assessed guilt, and evaluated confession voluntariness.
  • Judges responded to implicit and explicit harmless error measures.

Main Results:

  • Judges correctly identified high-pressure confessions as coerced and improperly admitted.
  • The presence of an improper confession significantly increased judicial conviction rates.
  • Judges demonstrated capability in performing harmless error analysis when required.

Conclusions:

  • Judges can identify coerced confessions but remain susceptible to their influence.
  • The harmless error analysis framework is manageable for appellate judges.
  • Further research is needed to mitigate the impact of improperly admitted evidence on judicial outcomes.