Multidimensional item Response theory to assess the psychometric properties of persian version of dutch eating behavior questionnaire (DEBQ) in university students

Author(s):  
Marziyeh Doostfatemeh ◽  
Elham Haem ◽  
Mohadeseh Sarbaraninan ◽  
Mehdi Ajdari Tafti
2020 ◽  
Author(s):  
Elham Haem ◽  
Marziyeh Doostfatemeh

Abstract Background: Multidimensional item response theory (MIRT) model provides an ideal foundation to assess psychological properties of a questionnaire designed with multidimensional structure. This study aimed to present the first use of MIRT models to investigate psychometric properties of general health questionnaire (GHQ-12) in parents of school children. Methods: A total of 1104 parents of school children completed the Persian version of GHQ-12 questionnaire. Unidimensional IRT model and MIRT models with two and three factors were applied to model the observed scores for each GHQ-12 item as a function of the subject’s latent traits while taking the correlation between dimensions of the questionnaire into account. The goodness of fit indices were reported for the three models, and items fit were assessed for the best model. Individual items were described in detail through item characteristic curves, and the amount of information carried by different items was presented using information curves. Results: The MIRT analysis with two factors corresponding to psychological distress and social dysfunction provided the best account of the GHQ-12 data. The model showed that all items were fitted adequately. Items varied in their discrimination ranged from 0.86 to 2.35 and 1.18 to 2.41 for psychological distress and social dysfunction, respectively. Moreover, items 8 and 2 provided the least information in psychological distress and social dysfunction dimensions, respectively. Conclusions: The developed framework to evaluate psychometric properties of GHQ-12 can be a suitable alternative to traditional approaches and also unidimensional IRT models, the use of which has been restricted due to multidimensional structure of the questionnaire.


2011 ◽  
Vol 35 (8) ◽  
pp. 604-622 ◽  
Author(s):  
Hirotaka Fukuhara ◽  
Akihito Kamata

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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