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

Statistical Hypothesis Testing01:16

Statistical Hypothesis Testing

2.0K
Hypothesis testing is a critical statistical procedure facilitating informed, evidence-based decisions. It begins with a hypothesis, which is a tentative explanation, or a prediction about a population parameter. This hypothesis can be either a null hypothesis (H0), indicating no effect or difference, or an alternative hypothesis (Ha), suggesting an effect or difference.
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
2.0K
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

155
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
155
Introduction to Test of Independence01:21

Introduction to Test of Independence

2.3K
In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
2.3K
Hypothesis Test for Test of Independence01:16

Hypothesis Test for Test of Independence

3.6K
The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...
3.6K
Multiple Comparison Tests01:13

Multiple Comparison Tests

3.9K
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...
3.9K
Goodness-of-Fit Test01:16

Goodness-of-Fit Test

3.4K
The goodness-of-fit test is a type of hypothesis test which determines whether the data "fits" a particular distribution. For example, one may suspect that some anonymous data may fit a binomial distribution. A chi-square test (meaning the distribution for the hypothesis test is chi-square) can be used to determine if there is a fit. The null and alternative hypotheses may be written in sentences or stated as equations or inequalities. The test statistic for a goodness-of-fit test is given as...
3.4K

You might also read

Related Articles

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

Sort by
Same author

Standard Error Estimation for Subpopulation Non-invariance.

Applied psychological measurement·2025
Same author

Investigating the Latent Structure of Executive Function in the Delis-Kaplan Executive Function System Using Cattell-Horn-Carroll Theory.

Assessment·2023
Same author

Diagnostic Test Score Validation With a Fallible Criterion.

Applied psychological measurement·2019
Same author

Integrating the switching, inhibition, and updating model of executive function with the Cattell-Horn-Carroll model.

Journal of experimental psychology. General·2015
Same author

A description of mixed group validation.

Assessment·2013
Same author

Considerations underlying the use of mixed group validation.

Psychological assessment·2012

Related Experiment Video

Updated: Jul 19, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.4K

Invited Commentary: Bayesian Inference with Multiple Tests.

Paul A Jewsbury1

  • 1Educational Testing Service, Foundational Psychometric and Statistical Research, 660 Rosedale Rd, M/s T-02, Princeton, NJ, 08541, USA. pjewsbury@ets.org.

Neuropsychology Review
|August 18, 2023
PubMed
Summary
This summary is machine-generated.

This study critiques malingering research, clarifying Bayesian diagnostic inference for neuropsychological practice. It refutes claims about simple Bayes models and offers new directions for research and clinical application.

Keywords:
BayesBayesianMultiple testsTest validationValidity

More Related Videos

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K
Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies
10:50

Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies

Published on: November 8, 2018

10.9K

Related Experiment Videos

Last Updated: Jul 19, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.4K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K
Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies
10:50

Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies

Published on: November 8, 2018

10.9K

Area of Science:

  • Neuropsychology
  • Psychometrics
  • Statistics

Background:

  • Critiques of malingering research and its implications for neuropsychological practice.
  • Focus on statistical issues in diagnostic inference with multiple tests.

Purpose of the Study:

  • To provide a balanced commentary on malingering research, addressing both critiques and existing literature.
  • To clarify Bayesian diagnostic inference and its application with multiple tests.
  • To refute specific conclusions from Leonhard's critique regarding statistical models.

Main Methods:

  • Review and analysis of existing malingering research literature.
  • Introduction and explanation of Bayesian diagnostic inference.
  • Discussion of assumptions underlying the simple Bayes model.
  • Critique of the chained likelihood ratios method.

Main Results:

  • Identified overlooked misconceptions and introduced new confusions in malingering literature.
  • Clarified misunderstandings and elucidated a valid approach to Bayesian inference.
  • Demonstrated the inappropriate application of the chained likelihood ratios method.
  • Refuted Leonhard's conclusions on incremental validity and the simple Bayes model.

Conclusions:

  • Bayesian diagnostic inference offers a valid approach for multiple tests in malingering assessment.
  • Specific statistical methods and interpretations in malingering research require revision.
  • Future research should focus on refining statistical applications and understanding diagnostic inference in neuropsychology.