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

Fisher's Exact Test01:08

Fisher's Exact Test

875
Fisher's exact test is a statistical significance test widely used to analyze 2x2 contingency tables, particularly in situations where sample sizes are small. Unlike the chi-squared test, which approximates P-values and assumes minimum expected frequencies of at least five in each cell, Fisher's exact test calculates the exact probability (P-value) of observing the data or more extreme results under the null hypothesis. This feature makes it especially valuable when the assumptions of...
875
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

3.9K
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).
3.9K
Behrens–Fisher Test00:57

Behrens–Fisher Test

146
The Behrens-Fisher test is a statistical method designed to address the Behrens-Fisher problem, which arises when comparing the means of two normally distributed populations with unequal variances. Unlike the Student's t-test, which assumes equal variances, the Behrens-Fisher test allows for mean comparison without this restrictive assumption. This flexibility makes it particularly valuable in scenarios where two independent samples exhibit normality but lack variance homogeneity.
This test...
146
F Distribution01:19

F Distribution

5.1K
The F distribution was named after Sir Ronald Fisher, an English statistician. The F statistic is a ratio (a fraction) with two sets of degrees of freedom; one for the numerator and one for the denominator. The F distribution is derived from the Student's t distribution. The values of the F distribution are squares of the corresponding values of the t distribution. One-Way ANOVA expands the t test for comparing more than two groups. The scope of that derivation is beyond the level of this...
5.1K
Goodness-of-Fit Test01:16

Goodness-of-Fit Test

5.5K
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...
5.5K
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

332
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
332

You might also read

Related Articles

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

Sort by
Same author

Using latent class analysis to justify a latent continuum in item development.

Psychological methods·2026
Same author

A Definition of a Heywood Case in Item Response Theory Based on Fisher Information.

Entropy (Basel, Switzerland)·2025
Same author

Individual factors and cisgender college students' attitudes and behaviors toward transgender individuals.

Journal of community psychology·2021
See all related articles

Related Experiment Video

Updated: Oct 15, 2025

Computerized Adaptive Testing System of Functional Assessment of Stroke
05:21

Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

6.0K

The Fisher information function and scoring in binary ideal point item response models: a cautionary tale.

Jay Verkuilen1

  • 1Ph.D. Program in Educational Psychology, The City University of New York Graduate Center, New York, USA.

The British Journal of Mathematical and Statistical Psychology
|October 23, 2021
PubMed
Summary

This study reveals inherent issues with Fisher information in ideal point item response models, impacting scoring accuracy. Caution is advised when using asymptotic methods for these models.

Keywords:
Fisher informationideal point modelsinformation theoryitem response theorylikelihood; psychometrics

More Related Videos

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

11.1K
A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing
15:00

A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing

Published on: February 7, 2025

810

Related Experiment Videos

Last Updated: Oct 15, 2025

Computerized Adaptive Testing System of Functional Assessment of Stroke
05:21

Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

6.0K
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

11.1K
A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing
15:00

A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing

Published on: February 7, 2025

810

Area of Science:

  • Psychometrics
  • Statistical Modeling

Background:

  • Binary ideal point item response models often exhibit bimodal Fisher information functions (FIMs) at the ideal point.
  • This bimodal property can lead to indeterminacy and violations of likelihood regularity conditions.

Purpose of the Study:

  • To examine the properties of Fisher information functions in binary ideal point item response models.
  • To explore the implications of these properties for model scoring and estimation.

Main Methods:

  • Theoretical analysis of Fisher information functions for ideal point item response models.
  • Investigation of model indeterminacy and regularity condition violations.

Main Results:

  • Fisher information functions in ideal point models are inherently bimodal or indeterminate.
  • These properties violate standard likelihood regularity conditions, affecting asymptotic inference.
  • Some models resolve indeterminacy but still violate regularity conditions; others show diverging FIMs.

Conclusions:

  • Ideal point item response models possess inherent Fisher information properties that necessitate caution in their application.
  • Asymptotic methods may be unreliable, especially for shorter assessments.
  • Recommended scoring methods include simulated plausible values or Bayesian estimation.