Related Experiment Video
Updated: Jul 17, 2025

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
Published on: September 27, 2019
Determining intra-standard-setter inconsistency in the Angoff method using the three-parameter item response theory
Mohsen Tavakol1, David O'Brien2, Claire Stewart2
1Medical Education Centre, School of Medicine, The University of Nottingham, UK.
This study used item response theory (IRT) to analyze Angoff ratings from medical students, finding standard-setters were generally consistent. This method helps reduce errors in educational assessments.
Area of Science:
- Medical Education
- Psychometrics
- Educational Assessment
Background:
- Standard-setting in medical education is crucial for determining pass marks.
- The Angoff method is widely used but can exhibit intra-standard-setter variability.
- Latent trait theory provides a framework for understanding assessment variability.
Discussion:
- This study applied the three-parameter item response theory (IRT) to analyze Angoff ratings from 358 medical students.
- The analysis focused on measuring intra-standard-setter variability and inter-standard-setter validity.
- Data were collected from two summative knowledge-based assessments.
Key Insights:
- The three-parameter IRT model effectively analyzes individual standard-setter results.
- Standard-setters demonstrated considerable consistency across both assessments.
- A strong positive correlation was observed between mean Angoff ratings and conditional probability, indicating inter-standard-setter validity.
Outlook:
- Adopting this IRT-based methodology can identify and minimize judgmental inconsistencies among standard-setters.
- This approach aids in reducing false positive and false negative decisions in educational assessments.
- Further research could explore the application of this methodology in diverse assessment contexts.
More Related Videos
14:14The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
Published on: May 13, 2022
09:00Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
Published on: August 16, 2024
Related Concept Videos
Friedman Two-way Analysis of Variance by Ranks
One-Way ANOVA: Equal Sample Sizes
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
One-Way ANOVA: Unequal Sample Sizes
Bonferroni Test
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
One-Way ANOVA