scholarly journals A Multidimensional Item Response Theory Model for Continuous and Graded Responses With Error in Persons and Items

2021 ◽  
pp. 001316442199841
Author(s):  
Pere J. Ferrando ◽  
David Navarro-González
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Theory Model ◽  
Response Model ◽  
Response Theory ◽  
Continuous Response ◽  
Graded Responses ◽  
Graded Response ◽  
Continuous Responses ◽  
Differential Measurement Error

Item response theory “dual” models (DMs) in which both items and individuals are viewed as sources of differential measurement error so far have been proposed only for unidimensional measures. This article proposes two multidimensional extensions of existing DMs: the M-DTCRM (dual Thurstonian continuous response model), intended for (approximately) continuous responses, and the M-DTGRM (dual Thurstonian graded response model), intended for ordered-categorical responses (including binary). A rationale for the extension to the multiple-content-dimensions case, which is based on the concept of the multidimensional location index, is first proposed and discussed. Then, the models are described using both the factor-analytic and the item response theory parameterizations. Procedures for (a) calibrating the items, (b) scoring individuals, (c) assessing model appropriateness, and (d) assessing measurement precision are finally discussed. The simulation results suggest that the proposal is quite feasible, and an illustrative example based on personality data is also provided. The proposals are submitted to be of particular interest for the case of multidimensional questionnaires in which the number of items per scale would not be enough for arriving at stable estimates if the existing unidimensional DMs were fitted on a separate-scale basis.

scholarly journals Reevaluation of the Amsterdam Inventory for Auditory Disability and Handicap Using Item Response Theory

2016 ◽  
Vol 59 (2) ◽  
pp. 373-383 ◽  
Author(s):  
J. Mirjam Boeschen Hospers ◽  
Niels Smits ◽  
Cas Smits ◽  
Mariska Stam ◽  
Caroline B. Terwee ◽  
...  
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Standard Error ◽  
Item Information ◽  
Response Model ◽  
Graded Response Model ◽  
Response Theory ◽  
Hearing Disability ◽  
Hearing Ability ◽  
Graded Response

Purpose We reevaluated the psychometric properties of the Amsterdam Inventory for Auditory Disability and Handicap (AIADH; Kramer, Kapteyn, Festen, & Tobi, 1995) using item response theory. Item response theory describes item functioning along an ability continuum. Method Cross-sectional data from 2,352 adults with and without hearing impairment, ages 18–70 years, were analyzed. They completed the AIADH in the web-based prospective cohort study “Netherlands Longitudinal Study on Hearing.” A graded response model was fitted to the AIADH data. Category response curves, item information curves, and the standard error as a function of self-reported hearing ability were plotted. Results The graded response model showed a good fit. Item information curves were most reliable for adults who reported having hearing disability and less reliable for adults with normal hearing. The standard error plot showed that self-reported hearing ability is most reliably measured for adults reporting mild up to moderate hearing disability. Conclusions This is one of the few item response theory studies on audiological self-reports. All AIADH items could be hierarchically placed on the self-reported hearing ability continuum, meaning they measure the same construct. This provides a promising basis for developing a clinically useful computerized adaptive test, where item selection adapts to the hearing ability of individuals, resulting in efficient assessment of hearing disability.

scholarly journals Optimal Examination Sites for Periodontal Disease Evaluation: Applying the Item Response Theory Graded Response Model

2020 ◽  
Vol 9 (11) ◽  
pp. 3754
Author(s):  
Yoshiaki Nomura ◽  
Toshiya Morozumi ◽  
Mitsuo Fukuda ◽  
Nobuhiro Hanada ◽  
Erika Kakuta ◽  
...  
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Complex Structure ◽  
Response Model ◽  
Graded Response Model ◽  
Response Theory ◽  
Graded Response ◽  
Periodontal Index ◽  
Selection Of

Periodontal examination data have a complex structure. For epidemiological studies, mass screenings, and public health use, a simple index that represents the periodontal condition is necessary. Periodontal indices for partial examination of selected teeth have been developed. However, the selected teeth vary between indices, and a justification for the selection of examination teeth has not been presented. We applied a graded response model based on the item response theory to select optimal examination teeth and sites that represent periodontal conditions. Data were obtained from 254 patients who participated in a multicenter follow-up study. Baseline data were obtained from initial follow-up. Optimal examination sites were selected using item information calculated by graded response modeling. Twelve sites—maxillary 2nd premolar (palatal-medial), 1st premolar (palatal-distal), canine (palatal-medial), lateral incisor (palatal-central), central incisor (palatal-distal) and mandibular 1st premolar (lingual, medial)—were selected. Mean values for clinical attachment level, probing pocket depth, and bleeding on probing by full mouth examinations were used for objective variables. Measuring the clinical parameters of these sites can predict the results of full mouth examination. For calculating the periodontal index by partial oral examination, a justification for the selection of examination sites is essential. This study presents an evidence-based partial examination methodology and its modeling.

scholarly journals Using the Stan Program for Bayesian Item Response Theory

2017 ◽  
Vol 78 (3) ◽  
pp. 384-408 ◽  
Author(s):  
Yong Luo ◽  
Hong Jiao
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Model Comparison ◽  
Response Model ◽  
Graded Response Model ◽  
Response Theory ◽  
Irt Model ◽  
Irt Models ◽  
Nominal Response Model ◽  
Graded Response

Stan is a new Bayesian statistical software program that implements the powerful and efficient Hamiltonian Monte Carlo (HMC) algorithm. To date there is not a source that systematically provides Stan code for various item response theory (IRT) models. This article provides Stan code for three representative IRT models, including the three-parameter logistic IRT model, the graded response model, and the nominal response model. We demonstrate how IRT model comparison can be conducted with Stan and how the provided Stan code for simple IRT models can be easily extended to their multidimensional and multilevel cases.

Item response theory analysis of the Pain Self-Efficacy Questionnaire

2017 ◽  
Vol 14 (1) ◽  
pp. 113-117 ◽  
Author(s):  
Daniel S.J. Costa ◽  
Ali Asghari ◽  
Michael K. Nicholas
Keyword(s):  
Item Response Theory ◽  
Psychometric Properties ◽  
Item Response ◽  
Self Efficacy ◽  
Latent Variable ◽  
Response Threshold ◽  
Response Model ◽  
Graded Response Model ◽  
Response Theory ◽  
Graded Response

AbstractBackground and aimsThe Pain Self-Efficacy Questionnaire (PSEQ) is a 10-item instrument designed to assess the extent to which a person in pain believes s/he is able to accomplish various activities despite their pain. There is strong evidence for the validity and reliability of both the full-length PSEQ and a 2-item version. The purpose of this study is to further examine the properties of the PSEQ using an item response theory (IRT) approach.MethodsWe used the two-parameter graded response model to examine the category probability curves, and location and discrimination parameters of the 10 PSEQ items. In item response theory, responses to a set of items are assumed to be probabilistically determined by a latent (unobserved) variable. In the graded-response model specifically, item response threshold (the value of the latent variable for which adjacent response categories are equally likely) and discrimination parameters are estimated for each item. Participants were 1511 mixed, chronic pain patients attending for initial assessment at a tertiary pain management centre.ResultsAll items except item 7 (‘I can cope with my pain without medication’) performed well in IRT analysis, and the category probability curves suggested that participants used the 7-point response scale consistently. Items 6 (‘I can still do many of the things I enjoy doing, such as hobbies or leisure activity, despite pain’), 8 (‘I can still accomplish most of my goals in life, despite the pain’) and 9 (‘I can live a normal lifestyle, despite the pain’) captured higher levels of the latent variable with greater precision.ConclusionsThe results from this IRT analysis add to the body of evidence based on classical test theory illustrating the strong psychometric properties of the PSEQ. Despite the relatively poor performance of Item 7, its clinical utility warrants its retention in the questionnaire.ImplicationsThe strong psychometric properties of the PSEQ support its use as an effective tool for assessing self-efficacy in people with pain.

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