Work

Comparing Approaches to Estimating Person Parameters for the MUPP Model

Year: 2025

Type: article

Abstract: This study compared maximum a posteriori (MAP), expected a posteriori (EAP), and Markov Chain Monte Carlo (MCMC) approaches to computing person scores from the Multi-Unidimensional Pairwise Preference Model. The MCMC approach used the No-U-Turn sampling (NUTS). Results suggested the EAP with fully crossed quadrature and the NUTS outperformed the others when there were fewer dimensions. In addition, the NUTS produced the most accurate estimates in larger dimension conditions. The number of items per dimension had the largest effect on person parameter recovery.

Source: Applied Psychological Measurement

DOI: 10.1177/01466216251316278

Authors: David M. LaHuis, Caitlin E. Blackmore, Gage M. Ammons

Institution: Wright State University

Language: English

Topic: Psychometric Methodologies and Testing

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W4406891246

FWCI:

Cites: 22

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Related to: 10