Jove
Visualize
Contact Us

Related Concept Videos

Probability Distributions01:32

Probability Distributions

7.7K
 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
7.7K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

2.6K
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).
2.6K
Choosing Between z and t Distribution01:25

Choosing Between z and t Distribution

2.9K
The z and the Student t distribution estimate the population mean using the sample mean and standard deviation. However, to decide which distribution to use for a calculation, one needs to determine the sample size, the nature of the distribution, and whether the population standard deviation is known. If the population standard deviation is known and the population is normally distributed, or if the sample size is greater than 30, the z distribution is preferred. The Student t distribution is...
2.9K
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

221
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
221
Reliability and Validity01:29

Reliability and Validity

12.8K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
12.8K
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

4.2K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
4.2K

You might also read

Related Articles

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

Sort by
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
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 Experiment Video

Updated: Aug 13, 2025

A Tactile Automated Passive-Finger Stimulator TAPS
19:44

A Tactile Automated Passive-Finger Stimulator TAPS

Published on: June 3, 2009

13.8K

Prior Distribution and Entropy in Computer Adaptive Testing Ability Estimation through MAP or EAP.

Joel Suárez-Cansino1, Virgilio López-Morales1, Luis Roberto Morales-Manilla2

  • 1Basic Sciences and Engineering Institute, Systems and Information Technologies Research Center, Intelligent Computing Research Group, Autonomous University of Hidalgo State, Col. Carboneras, Mineral de la Reforma 42184, Hidalgo, Mexico.

Entropy (Basel, Switzerland)
|January 21, 2023
PubMed
Summary

This study enhances computer adaptive testing (CAT) by integrating academic performance data with maximum entropy theory. This approach improves the accuracy of deriving latent traits like ability, optimizing test item selection.

Keywords:
Bayesian inferenceCATKullback–Leibler divergenceentropyexpectation a posterioriitem characteristic curveitem response theorylikelihood functionmaximum a posterioriperformance index function

More Related Videos

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

5.9K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.7K

Related Experiment Videos

Last Updated: Aug 13, 2025

A Tactile Automated Passive-Finger Stimulator TAPS
19:44

A Tactile Automated Passive-Finger Stimulator TAPS

Published on: June 3, 2009

13.8K
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

5.9K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.7K

Area of Science:

  • Educational Measurement
  • Psychometrics
  • Information Theory

Background:

  • Computer adaptive testing (CAT) relies on calibrated item sets to estimate examinee ability.
  • Existing models often use conditional probability based on response history (hits/misses).
  • Accurate latent trait derivation is crucial for effective CAT.

Purpose of the Study:

  • To integrate experimental academic performance data with maximum entropy theory in CAT.
  • To develop academic performance index functions for improved prior distribution selection.
  • To explore the conditions for using constrained versus personalized prior distributions.

Main Methods:

  • Developed academic performance index functions based on experimental and historical data.
  • Integrated these functions into a maximum entropy framework.
  • Analyzed the conditions for applying constrained prior distributions in CAT.

Main Results:

  • Demonstrated the integration of experimental data with maximum entropy for latent trait derivation.
  • Showcased the utility of performance index functions in CAT.
  • Identified limitations of heuristic prior distributions and conditions for personalized priors.

Conclusions:

  • The proposed method enhances CAT by incorporating empirical performance data via maximum entropy.
  • Academic performance index functions improve the selection of prior distributions.
  • Personalized prior distributions are recommended over heuristic ones in specific scenarios.