Comments on ‘Longitudinal Analysis of Patient-Reported Outcomes in Clinical Trials: Applications of Multilevel and Multidimensional Item Response Theory’

Psychometrika ◽  
2021 ◽  
Author(s):  
Karl Bang Christensen
Keyword(s):  
Clinical Trials ◽  
Item Response Theory ◽  
Item Response ◽  
Longitudinal Analysis ◽  
Patient Reported Outcomes ◽  
Multidimensional Item Response Theory ◽  
Multidimensional Item Response ◽  
Response Theory ◽  
Patient Reported

Estimating Power for Clinical Trials with Patient Reported Outcomes - using Item Response Theory

2021 ◽  
Author(s):  
Jinxiang Hu ◽  
Jeffrey Thompson ◽  
Dinesh Pal Mudaranthakam ◽  
Lynn Chollet Hinton ◽  
David Streeter ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Item Response Theory ◽  
Item Response ◽  
Patient Reported Outcomes ◽  
Response Theory ◽  
Patient Reported

A Bifactor Multidimensional Item Response Theory Model for Differential Item Functioning Analysis on Testlet-Based Items

2011 ◽  
Vol 35 (8) ◽  
pp. 604-622 ◽  
Author(s):  
Hirotaka Fukuhara ◽  
Akihito Kamata
Keyword(s):  
Item Response Theory ◽  
Differential Item Functioning ◽  
Item Response ◽  
Estimation Method ◽  
Multidimensional Item Response Theory ◽  
Multidimensional Item Response ◽  
Response Theory ◽  
Data Set ◽  
Detection Rates ◽  
Item Functioning

A differential item functioning (DIF) detection method for testlet-based data was proposed and evaluated in this study. The proposed DIF model is an extension of a bifactor multidimensional item response theory (MIRT) model for testlets. Unlike traditional item response theory (IRT) DIF models, the proposed model takes testlet effects into account, thus estimating DIF magnitude appropriately when a test is composed of testlets. A fully Bayesian estimation method was adopted for parameter estimation. The recovery of parameters was evaluated for the proposed DIF model. Simulation results revealed that the proposed bifactor MIRT DIF model produced better estimates of DIF magnitude and higher DIF detection rates than the traditional IRT DIF model for all simulation conditions. A real data analysis was also conducted by applying the proposed DIF model to a statewide reading assessment data set.

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