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

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.8K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.8K
Comparative Excretory Systems02:24

Comparative Excretory Systems

26.7K
Animals have evolved different strategies for excretion, the removal of waste from the body. Most waste must be dissolved in water to be excreted, so an animal’s excretory strategy directly affects its water balance.
26.7K
Comparing Experimental Results: Student's t-Test01:09

Comparing Experimental Results: Student's t-Test

6.1K
The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
6.1K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

609
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
609
Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

16.8K
The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
16.8K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.6K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.6K

You might also read

Related Articles

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

Sort by
Same author

International Test Commission guidelines for test adaptation: A criterion checklist.

Psicothema·2020
Same author

Profiles of Mathematics Anxiety Among 15-Year-Old Students: A Cross-Cultural Study Using Multi-Group Latent Profile Analysis.

Frontiers in psychology·2019
Same author

Detecting Item Preknowledge Using a Predictive Checking Method.

Applied psychological measurement·2018
Same author

The Effect of Rating Unfamiliar Items on Angoff Passing Scores.

Educational and psychological measurement·2018
Same author

Practical Consequences of Item Response Theory Model Misfit in the Context of Test Equating with Mixed-Format Test Data.

Frontiers in psychology·2017
Same author

Tracking functional status across the spinal cord injury lifespan: linking pediatric and adult patient-reported outcome scores.

Archives of physical medicine and rehabilitation·2014

Related Experiment Video

Updated: Feb 10, 2026

Qualitative and Comparative Cortical Activity Data Analyses from a Functional Near-Infrared Spectroscopy Experiment Applying Block Design
06:18

Qualitative and Comparative Cortical Activity Data Analyses from a Functional Near-Infrared Spectroscopy Experiment Applying Block Design

Published on: December 3, 2020

4.4K

Comparative Analyses of MIRT Models and Software (BMIRT and flexMIRT).

Guler Yavuz1, Ronald K Hambleton2

  • 1Adiyaman University, Adiyaman, Turkey.

Educational and Psychological Measurement
|May 26, 2018
PubMed
Summary

This study compared parameter recovery in MIRT software (BMIRT, flexMIRT) using Bock-Aitkin EM, MCMC, and MH-RM algorithms. All methods showed similar accuracy with large sample sizes and test lengths, though BA-EM offered faster estimation.

Keywords:
BA-EMBMIRTMCMCMH-RMflexMIRTitem parameter recoverymultidimensional item response theory

More Related Videos

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

Published on: May 9, 2017

9.6K
Fish Sperm Assessment Using Software and Cooling Devices
07:57

Fish Sperm Assessment Using Software and Cooling Devices

Published on: July 28, 2018

9.3K

Related Experiment Videos

Last Updated: Feb 10, 2026

Qualitative and Comparative Cortical Activity Data Analyses from a Functional Near-Infrared Spectroscopy Experiment Applying Block Design
06:18

Qualitative and Comparative Cortical Activity Data Analyses from a Functional Near-Infrared Spectroscopy Experiment Applying Block Design

Published on: December 3, 2020

4.4K
Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

Published on: May 9, 2017

9.6K
Fish Sperm Assessment Using Software and Cooling Devices
07:57

Fish Sperm Assessment Using Software and Cooling Devices

Published on: July 28, 2018

9.3K

Area of Science:

  • Educational Measurement and Psychometrics
  • Statistical Modeling

Background:

  • Accurate parameter estimation is crucial for Multiple-Imputation Repeated-Measures (MIRT) modeling.
  • Software packages like BMIRT and flexMIRT are widely used for MIRT analysis.
  • Different estimation algorithms (e.g., EM, MCMC) can impact parameter recovery quality.

Purpose of the Study:

  • To investigate and compare the model parameter recovery of BMIRT and flexMIRT software.
  • To evaluate the performance of Bock-Aitkin EM (BA-EM), Markov chain Monte Carlo (MCMC), and Metropolis-Hastings Robbins-Monro (MH-RM) algorithms within these packages.
  • To understand how measurement conditions affect parameter estimation accuracy.

Main Methods:

  • Comparative analysis of MIRT software (BMIRT, flexMIRT).
  • Implementation of three distinct item parameter estimation techniques: BA-EM, MCMC, and MH-RM.
  • Simulation study under varying conditions of sample size, test length, and number of dimensions.

Main Results:

  • All tested estimation techniques yielded comparable root mean square error values under conditions of large sample size and high test length.
  • Each estimation technique demonstrated specific strengths and weaknesses contingent on the number of dimensions, sample size, and test length.
  • The BA-EM technique consistently exhibited the shortest estimation time across all tested conditions.

Conclusions:

  • The choice of MIRT software and estimation algorithm impacts parameter recovery and computational efficiency.
  • BA-EM provides a computationally efficient option for MIRT parameter estimation, particularly when speed is a consideration.
  • Researchers should consider the interplay of sample size, test length, and dimensionality when selecting an MIRT estimation technique for optimal results.