scholarly journals Modeling Response Style Using Vignettes and Person-Specific Item Response Theory

2018 ◽  
Vol 43 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Katherine G. Jonas ◽  
Kristian E. Markon
Keyword(s):  
Item Response ◽  
Simulated Data ◽  
Response Style ◽  
Response Styles ◽  
Personality Pathology ◽  
Graded Response Model ◽  
Graded Response ◽  
Attitudinal Data ◽  
Comparative Accuracy ◽  
Item Characteristics

Responses to survey data are determined not only by item characteristics and respondents’ trait standings but also by response styles. Recently, methods for modeling response style with personality and attitudinal data have turned toward the use of anchoring vignettes, which provide fixed rating targets. Although existing research is promising, a few outstanding questions remain. First, it is not known how many vignettes and vignette ratings are necessary to identify response style parameters. Second, the comparative accuracy of these models is largely unexplored. Third, it remains unclear whether correcting for response style improves criterion validity. Both simulated data and data observed from a population-representative sample responding to a measure of personality pathology (the Personality Inventory for DSM-5 [PID-5]) were modeled using an array of response style models. In simulations, most models estimating response styles outperformed the graded response model (GRM), and in observed data, all response style models were superior to the GRM. Correcting for response style had a small, but in some cases significant, effect on the prediction of self-reported social dysfunction.

scholarly journals Accounting for Item Response Process and Response Styles Using the Unfolding Item Response Tree (UIRTree) Model

2021 ◽  
Author(s):  
Zhaojun Li ◽  
Bo Zhang ◽  
Mengyang Cao ◽  
Louis Tay
Keyword(s):  
Item Response ◽  
Response Styles ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Response Process ◽  
Monte Carlo Simulation Study ◽  
Graded Response ◽  
Extreme Response ◽  
Generalized Graded Unfolding Model ◽  
Unfolding Models

Many researchers have found that unfolding models may better represent how respondents answer Liker-type items and response styles (RSs) often have moderate to strong presence in responses to such items. However, the two research lines have been growing largely in parallel. The present study proposed an unfolding item response tree (UIRTree) model that can account for unfolding response process and RSs simultaneously. An empirical illustration showed that the UIRTree model could fit a personality dataset well and produced more reasonable parameter estimates. Strong presence of the extreme response style (ERS) was also revealed by the UIRTree model. We further conducted a Monte Carlo simulation study to examine the performance of the UIRTree model compared to three other models for Likert-scale responses: the Samejima’s graded response model, the generalized graded unfolding model, and the dominance item response tree (DIRTree) model. Results showed that when data followed unfolding response process and contained the ERS, the AIC was able to select the UIRTree model, while BIC was biased towards the DIRTree model in many conditions. In addition, model parameters in the UIRTree model could be accurately recovered under realistic conditions, and wrongly assuming the item response process or ignoring RSs was detrimental to the estimation of key parameters. In general, the UIRTree model is expected to help in better understanding of responses to Liker-type items theoretically and contribute to better scale development practically. Future studies on multi-trait UIRTree models and UIRTree models accounting for different types of RSs are expected.

An IRT Analysis of the Personal Optimism Scale

2008 ◽  
Vol 24 (1) ◽  
pp. 49-56 ◽  
Author(s):  
Wolfgang A. Rauch ◽  
Karl Schweizer ◽  
Helfried Moosbrugger
Keyword(s):  
Item Response ◽  
Data Model ◽  
Latent Trait ◽  
Model Fit ◽  
Response Functions ◽  
Graded Response Model ◽  
Irt Model ◽  
Item Parameters ◽  
Graded Response ◽  
Personal Optimism

Abstract. In this study the psychometric properties of the Personal Optimism scale of the POSO-E questionnaire ( Schweizer & Koch, 2001 ) for the assessment of dispositional optimism are evaluated by applying Samejima's (1969) graded response model, a parametric item response theory (IRT) model for polytomous data. Model fit is extensively evaluated via fit checks on the lower-order margins of the contingency table of observed and expected responses and visual checks of fit plots comparing observed and expected category response functions. The model proves appropriate for the data; a small amount of misfit is interpreted in terms of previous research using other measures for optimism. Item parameters and information functions show that optimism can be measured accurately, especially at moderately low to middle levels of the latent trait scale, and particularly by the negatively worded items.

scholarly journals A Note on the D-Scoring Method Adapted for Polytomous Test Items

2018 ◽  
Vol 79 (3) ◽  
pp. 545-557 ◽  
Author(s):  
Dimiter M. Dimitrov ◽  
Yong Luo
Keyword(s):  
Item Response ◽  
Psychological Assessment ◽  
Response Model ◽  
Response Functions ◽  
Graded Response Model ◽  
Unified Framework ◽  
Polytomous Items ◽  
Scoring Method ◽  
Test Items ◽  
Graded Response

An approach to scoring tests with binary items, referred to as D-scoring method, was previously developed as a classical analog to basic models in item response theory (IRT) for binary items. As some tests include polytomous items, this study offers an approach to D-scoring of such items and parallels the results with those obtained under the graded response model (GRM) for ordered polytomous items in the framework of IRT. The proposed design of using D-scoring with “virtual” binary items generated from polytomous items provides (a) ability scores that are consistent with their GRM counterparts and (b) item category response functions analogous to those obtained under the GRM. This approach provides a unified framework for D-scoring and psychometric analysis of tests with binary and/or polytomous items that can be efficient in different scenarios of educational and psychological assessment.

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 Performance of longitudinal item response theory models in shortened or partial assessments

2020 ◽  
Vol 47 (5) ◽  
pp. 461-471
Author(s):  
Leticia Arrington ◽  
Sebastian Ueckert ◽  
Malidi Ahamadi ◽  
Sreeraj Macha ◽  
Mats O. Karlsson
Keyword(s):  
Disease Progression ◽  
Item Response ◽  
Drug Effect ◽  
Simulated Data ◽  
Real Data ◽  
Item Information ◽  
Item Characteristics ◽  
The Impact ◽  
Substantial Change ◽  
Longitudinal Item Response

Abstract This work evaluates the performance of longitudinal item response (IR) theory models in shortened assessments using an existing model for part II and III of the MDS-UPDRS score. Based on the item information content, the assessment was reduced by removal of items in multiple increments and the models’ ability to recover the item characteristics of the remaining items at each level was evaluated. This evaluation was done for both simulated and real data. The metric of comparison in both cases was the item information function. For real data, the impact of shortening on the estimated disease progression and drug effect was also studied. In the simulated data setting, the item characteristics did not differ between the full and the shortened assessments down to the lowest level of information remaining; indicating a considerable independence between items. In contrast when reducing the assessment in a real data setting, a substantial change in item information was observed for some of the items. Disease progression and drug effect estimates also decreased in the reduced assessments. These changes indicate a shift in the measured construct of the shortened assessment and warrant caution when comparing results from a partial assessment with results from the full assessment.

Quantification of Experienced Hearing Problems With Item Response Theory

2013 ◽  
Vol 22 (2) ◽  
pp. 252-262 ◽  
Author(s):  
Michelene Chenault ◽  
Martijn Berger ◽  
Bernd Kremer ◽  
Lucien Anteunis
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Patient Reported Outcomes ◽  
Graded Response Model ◽  
Response Theory ◽  
Discriminative Ability ◽  
Graded Response ◽  
Patient Reported ◽  
Best Fit ◽  
Selection Of

Purpose The purpose of this study was to improve the effectiveness of adult hearing screens and demonstrate that interventions assessment methods are needed that address the individual's experienced hearing. Item response theory, which provides a methodology for assessing patient-reported outcomes, is examined here to demonstrate its usefulness in hearing screens and interventions. Method The graded response model is applied to a scale of 11 items assessing perceived hearing functioning and 10 items assessing experienced social limitations completed by a sample of 212 persons age 55+ years. Fixed and variable slope models are compared. Discrimination and threshold parameters are estimated and information functions evaluated. Results Variable slope models for both scales provided the best fit. The estimated discrimination parameters for all items except for one in each scale were good if not excellent (1.5–3.4). Threshold values varied, demonstrating the complementary and supplementary value of items within a scale. The information provided by each item varies relative to trait values so that each scale of items provides information over a wider range of trait values. Conclusion Item response theory methodology facilitates the comparison of items relative to their discriminative ability and information provided and thus provides a basis for the selection of items for application in a screening setting.

scholarly journals Use of item response theory to investigate disability-related questions in the National Health and Nutrition Examination Survey

2021 ◽  
Vol 9 ◽  
pp. 205031212110122
Author(s):  
Samuel W Terman ◽  
James F Burke
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
National Health ◽  
Activity Limitations ◽  
Response Model ◽  
Nutrition Examination Survey ◽  
Graded Response Model ◽  
Health And Nutrition ◽  
Graded Response ◽  
Two Parameter

Objectives: Accurately measuring disability is critical toward policy development, economic analyses, and determining individual-level effects of health interventions. Nationally representative population surveys such as the National Health and Nutrition Examination Survey provide key opportunities to measure disability constructs such as activity limitations. However, only very limited work has previously evaluated the item response properties of questions pertaining to limitations in National Health and Nutrition Examination Survey. Methods: This was a cross-sectional study. We included participants ⩾20 years old for the 2013–2018 National Health and Nutrition Examination Survey cycles. Activity limitations, and a smaller number of body function impairments or participation restrictions, were determined from interview questions. We performed item response theory models (a two-parameter logistic and a graded response model) to characterize discriminating information along the latent continuum of activity limitation. Results: We included 17,057 participants. Although each particular limitation was somewhat rare (maximally 13%), 7214 (38%) responded having at least one limitation. We found a high amount of discriminating information at 1–2 standard deviations above average limitation, though essentially zero discrimination below that range. Items had substantial overlap in the range at which they provided information distinguishing individuals. The ordinal graded response model including 20 limitations provided greater information than the dichotomous two-parameter logistic model, though further omitting items from the graded response model led to loss of information. Conclusion: National Health and Nutrition Examination Survey disability-related questions, mostly specifically activity limitations, provided a high degree of information distinguishing individuals with higher than average limitations on the latent continuum, but essentially zero resolution to distinguish individuals with low or average limitations. Future work may focus on developing items which better distinguish individuals at the “lower” end of the limitation spectrum.

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.

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