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{"work":{"id":117308947,"created_at":"2024-04-10T05:32:20.008-07:00","from_world_paper_id":252687578,"updated_at":"2024-11-25T15:16:37.386-08:00","_data":{"publisher":"Springer New York","grobid_abstract":"A new item response model is proposed for which the trait is positive. Three such models, the loglogistic, the log-normal, and the Weibull, are presented along with their item information curves. The data of seven addiction items from the DSM-IV from a study on alcohol addiction is analyzed by these three models using Bayesian Markov chain Monte Carlo methods. The item characteristic curves and item information curves are presented for all three models. The person scores for four item response patterns are presented for the log-logistic model.","publication_date":"2013,,","publication_name":"Springer Proceedings in Mathematics \u0026 Statistics","grobid_abstract_attachment_id":"113199508"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Positive Trait Item Response Models","broadcastable":false,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [302690343]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; window.loginModal = {}; window.loginModal.appleClientId = 'edu.academia.applesignon'; window.userInChina = "false";</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":113199508,"attachmentType":"pdf"}"><img alt="First page of “Positive Trait Item Response Models”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/113199508/mini_magick20240802-1-t1z6md.png?1722639133" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/images/single_work_splash/adobe_icon.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Positive Trait Item Response Models</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="302690343" href="https://independent.academia.edu/LuckeJ"><img alt="Profile image of Joseph Lucke" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/302690343/147852323/137407684/s65_joseph.lucke.png" />Joseph Lucke</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">2013, Springer Proceedings in Mathematics & Statistics</p><div class="ds-work-card--work-metadata"><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">visibility</span><p class="ds2-5-body-sm" id="work-metadata-view-count">…</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">description</span><p class="ds2-5-body-sm">8 pages</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">link</span><p class="ds2-5-body-sm">1 file</p></div></div><script>(async () => { const workId = 117308947; const worksViewsPath = "/v0/works/views?subdomain_param=api&work_ids%5B%5D=117308947"; const getWorkViews = async (workId) => { const response = await fetch(worksViewsPath); if (!response.ok) { throw new Error('Failed to load work views'); } const data = await response.json(); return data.views[workId]; }; // Get the view count for the work - we send this immediately rather than waiting for // the DOM to load, so it can be available as soon as possible (but without holding up // the backend or other resource requests, because it's a bit expensive and not critical). const viewCount = await getWorkViews(workId); const updateViewCount = (viewCount) => { try { const viewCountNumber = parseInt(viewCount, 10); if (viewCountNumber === 0) { // Remove the whole views element if there are zero views. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); return; } const commaizedViewCount = viewCountNumber.toLocaleString(); const viewCountBody = document.getElementById('work-metadata-view-count'); if (!viewCountBody) { throw new Error('Failed to find work views element'); } viewCountBody.textContent = `${commaizedViewCount} views`; } catch (error) { // Remove the whole views element if there was some issue parsing. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); throw new Error(`Failed to parse view count: ${viewCount}`, error); } }; // If the DOM is still loading, wait for it to be ready before updating the view count. if (document.readyState === "loading") { document.addEventListener('DOMContentLoaded', () => { updateViewCount(viewCount); }); // Otherwise, just update it immediately. } else { updateViewCount(viewCount); } })();</script></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">A new item response model is proposed for which the trait is positive. Three such models, the loglogistic, the log-normal, and the Weibull, are presented along with their item information curves. The data of seven addiction items from the DSM-IV from a study on alcohol addiction is analyzed by these three models using Bayesian Markov chain Monte Carlo methods. The item characteristic curves and item information curves are presented for all three models. The person scores for four item response patterns are presented for the log-logistic model.</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":113199508,"attachmentType":"pdf","workUrl":"https://www.academia.edu/117308947/Positive_Trait_Item_Response_Models"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":113199508,"attachmentType":"pdf","workUrl":"https://www.academia.edu/117308947/Positive_Trait_Item_Response_Models"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div><div class="ds-signup-banner-trigger-container"><div class="ds-signup-banner-trigger ds-signup-banner-trigger-control"></div></div><div class="ds-signup-banner ds-signup-banner-control"><div id="ds-signup-banner-close-button"><button class="ds2-5-button ds2-5-button--secondary ds2-5-button--inverse"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">close</span></button></div><div class="ds-signup-banner-ctas"><img src="//a.academia-assets.com/images/academia-logo-capital-white.svg" /><h4 class="ds2-5-heading-serif-sm">Sign up for access to the world's latest research</h4><button class="ds2-5-button ds2-5-button--inverse ds2-5-button--full-width js-swp-download-button" data-signup-modal="{"location":"signup-banner"}">Sign up for free<span class="material-symbols-outlined" style="font-size: 20px" translate="no">arrow_forward</span></button></div><div class="ds-signup-banner-divider"></div><div class="ds-signup-banner-reasons"><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Get notified about relevant papers</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Save papers to use in your research</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Join the discussion with peers</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Track your impact</span></div></div></div><script>(() => { // Set up signup banner show/hide behavior: // 1. 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The sample consisted of 292 men and 140 women who qualified for a Diagnostic and Statistical Manual of Mental Disorders (3rd ed., rev.; American Psychiatric Association, 1987) substance use disorder (SUD) diagnosis and 293 men and 445 women who did not qualify for a SUD diagnosis. The results indicated that men had a higher probability of endorsing substance use compared with women. The index significantly predicted health, psychiatric, and psychosocial disturbances as well as level of substance use behavior and severity of SUD after a 2-year follow-up. Finally, this index is a reliable and useful prognostic indicator of the risk for SUD and the medical and psychosocial sequelae of drug consumption.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Item response theory modeling of substance use: An index based on 10 drug categories","attachmentId":88730248,"attachmentType":"pdf","work_url":"https://www.academia.edu/83361016/Item_response_theory_modeling_of_substance_use_An_index_based_on_10_drug_categories","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/83361016/Item_response_theory_modeling_of_substance_use_An_index_based_on_10_drug_categories"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="10113697" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/10113697/Application_of_item_response_theory_to_quantify_substance_use_disorder_severity">Application of item response theory to quantify substance use disorder severity</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="24664697" href="https://pitt.academia.edu/MichaelVanyukov">Michael Vanyukov</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Addictive Behaviors, 2006</p><p class="ds-related-work--abstract ds2-5-body-sm">Objective: The present investigation had two main goals: (1) Determine whether binary substance use disorder (SUD) diagnoses are indicators of a unidimensional trait indexing severity of disorder; and, (2) demonstrate the predictive, concurrent and construct validity of the SUD severity scale. Methods: Boys and their biological parents were administered structured diagnostic interviews to diagnose SUD. Item response theory (IRT) was applied to determine whether the diagnoses are indicators of a unidimensional trait. The score on this scale was correlated with substance use behavior, violence, treatment history, risky sex, and social adjustment. Results: SUD diagnoses are indicators of a unidimensional latent trait. Maternal and paternal SUD severity predicted son's SUD severity at age 19. The score on the SUD severity scale correlated with drug use frequency, number of different drugs used in lifetime, treatment seeking, illegal behavior, social maladjustment, and risky sex. Conclusion: SUD can be quantified on an interval scale indexing severity of disorder. The advantages of measuring SUD severity as a continuous trait are discussed. D</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Application of item response theory to quantify substance use disorder severity","attachmentId":47525137,"attachmentType":"pdf","work_url":"https://www.academia.edu/10113697/Application_of_item_response_theory_to_quantify_substance_use_disorder_severity","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/10113697/Application_of_item_response_theory_to_quantify_substance_use_disorder_severity"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="115318735" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/115318735/The_Person_Response_Curve_Fit_of_Individuals_to_Item_Characteristic_Curve_Models">The Person Response Curve: Fit of Individuals to Item Characteristic Curve Models</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="298623493" href="https://independent.academia.edu/TomTrabin">Tom Trabin</a></div><p class="ds-related-work--metadata ds2-5-body-xs">1979</p><p class="ds-related-work--abstract ds2-5-body-sm">Bejar , I. I., & Weiss , D. J. Computer programs for scoring test data with item characteristic curve models (Research Report 79-1</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"The Person Response Curve: Fit of Individuals to Item Characteristic Curve Models","attachmentId":111761054,"attachmentType":"pdf","work_url":"https://www.academia.edu/115318735/The_Person_Response_Curve_Fit_of_Individuals_to_Item_Characteristic_Curve_Models","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/115318735/The_Person_Response_Curve_Fit_of_Individuals_to_Item_Characteristic_Curve_Models"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="7767335" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/7767335/Estimation_of_a_four_parameter_item_response_theory_model">Estimation of a four-parameter item response theory model</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="14276709" href="https://uncg.academia.edu/KellyRulison">Kelly Rulison</a></div><p class="ds-related-work--metadata ds2-5-body-xs">British Journal of Mathematical & Statistical Psychology, 2009</p><p class="ds-related-work--abstract ds2-5-body-sm">We explore the justification and formulation of a four-parameter item response theory model (4PM) and employ a Bayesian approach to recover successfully parameter estimates for items and respondents. For data generated using a 4PM item response model, overall fit is improved when using the 4PM rather than the 3PM or the 2PM. Furthermore, although estimated trait scores under the various models correlate almost perfectly, inferences at the high and low ends of the trait continuum are compromised, with poorer coverage of the confidence intervals when the wrong model is used. We also show in an empirical example that the 4PM can yield new insights into the properties of a widely used delinquency scale. We discuss the implications for building appropriate measurement models in education and psychology to model more accurately the underlying response process.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Estimation of a four-parameter item response theory model","attachmentId":48347639,"attachmentType":"pdf","work_url":"https://www.academia.edu/7767335/Estimation_of_a_four_parameter_item_response_theory_model","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/7767335/Estimation_of_a_four_parameter_item_response_theory_model"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="15065951" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/15065951/Fitting_a_Two_Parameter_Logistic_Item_Response_Model_to_Clarify_the_Psychometric_Properties_of_the_Drug_Use_Screening_Inventory_for_Adolescent_Alcohol_and_Drug_Abusers">Fitting a Two-Parameter Logistic Item Response Model to Clarify the Psychometric Properties of the Drug Use Screening Inventory for Adolescent Alcohol and Drug Abusers</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="34094519" href="https://independent.academia.edu/RalphTarter">Ralph Tarter</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="34183526" href="https://independent.academia.edu/LeventKirisci">Levent Kirisci</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Alcoholism: Clinical and Experimental Research, 1994</p><p class="ds-related-work--abstract ds2-5-body-sm">The suitability of fitting a two-parameter logistic item response model to the Drug Use Screening Inventory (DUSI) was assessed. In a sample of 846 adolescents, each of the 10 domains was found to be unidimensional. lnvariance of the item parameters across different groups was also observed. The reliability coefficient, based on item response theory, was found to be superior. The results of these analyses indicate that the DUSI has sound psychometric properties.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Fitting a Two-Parameter Logistic Item Response Model to Clarify the Psychometric Properties of the Drug Use Screening Inventory for Adolescent Alcohol and Drug Abusers","attachmentId":43607174,"attachmentType":"pdf","work_url":"https://www.academia.edu/15065951/Fitting_a_Two_Parameter_Logistic_Item_Response_Model_to_Clarify_the_Psychometric_Properties_of_the_Drug_Use_Screening_Inventory_for_Adolescent_Alcohol_and_Drug_Abusers","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/15065951/Fitting_a_Two_Parameter_Logistic_Item_Response_Model_to_Clarify_the_Psychometric_Properties_of_the_Drug_Use_Screening_Inventory_for_Adolescent_Alcohol_and_Drug_Abusers"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="91190707" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/91190707/A_new_family_of_asymmetric_models_for_Item_Response_Theory_a_Skew_Normal_IRT_Family">A new family of asymmetric models for Item Response Theory: a Skew-Normal IRT Family</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="246290831" href="https://independent.academia.edu/M%C3%A1rciaBranco1">Márcia Branco</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2004</p><p class="ds-related-work--abstract ds2-5-body-sm">Normal assumptions for the latent variable and symmetric item characteristics curves have been used in the last 50 years in many psychometric methods for item-response theory (IRT) models. This paper introduces a new family of asymmetric models for item response theory, namely the skew-normal item-response theory (SN-IRT) model. This family extends the ogive normal (symmetric probit-normal) model by considering: a) an accumulated skew-normal distribution for the item characteristic curve and b) skew-normal distributions are assumed as priors for latent variables for modeling individuals' ability. Four models compose the SN-IRT family: skewprobit-skew-normal, skew-probit-normal, probit-skew-normal and probit-normal models as a particular case. Hence, the SN-IRT is a more flexible model for fitting data sets with dichotomous responses. Bayesian inference methodology using two data augmentation approaches for implementing the MCMC methodology is developed. Model selection between symmetric and asymmetric models is considered by using the deviance information criterion (DIC) and the expected AIC and expected BIC and by using latent residuals. The proposed penalization (asymmetry) parameter is interpreted in the context of a particular data set related to a mathematical test. Suggestions for use the in news applications of skew probit propose in the paper are discussed.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A new family of asymmetric models for Item Response Theory: a Skew-Normal IRT Family","attachmentId":94547833,"attachmentType":"pdf","work_url":"https://www.academia.edu/91190707/A_new_family_of_asymmetric_models_for_Item_Response_Theory_a_Skew_Normal_IRT_Family","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/91190707/A_new_family_of_asymmetric_models_for_Item_Response_Theory_a_Skew_Normal_IRT_Family"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="25986476" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/25986476/Bayesian_Item_Response_Modeling_Theory_and_Applications_by_Jean_Paul_Fox">Bayesian Item Response Modeling: Theory and Applications by Jean-Paul Fox</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="43488748" href="https://independent.academia.edu/JeanPaulFox">Jean-Paul Fox</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Statistical Review, 2011</p><p class="ds-related-work--abstract ds2-5-body-sm">Jean-Paul Fox Springer, 2010, xiv + 313 pages, £53.99/€59.95/$69.95, hardcover ISBN: 978-1-4419-0741-7 Table of contents 1. Introduction to Bayesian item response modeling 2. Bayesian hierarchical response modeling 3. Basic elements of Bayesian statistics 4. Estimation of Bayesian item response models 5. Assessment of Bayesian item response models 6. Multilevel item response theory models 7. Random item effects models 8. Response time item response models 9. Randomized item response models Readership: Researchers (including applied statisticians, psychometricians, and social scientists) as well as graduate students interested in Bayesian Item Response Theory.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Bayesian Item Response Modeling: Theory and Applications by Jean-Paul Fox","attachmentId":46337002,"attachmentType":"pdf","work_url":"https://www.academia.edu/25986476/Bayesian_Item_Response_Modeling_Theory_and_Applications_by_Jean_Paul_Fox","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/25986476/Bayesian_Item_Response_Modeling_Theory_and_Applications_by_Jean_Paul_Fox"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="6327078" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/6327078/Recovery_of_Two_and_Three_Parameter_Logistic_Item_Characteristic_Curves_A_Monte_Carlo_Study">Recovery of Two and Three-Parameter Logistic Item Characteristic Curves: A Monte Carlo Study</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="9843286" href="https://independent.academia.edu/RobinLissak">Robin Lissak</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Applied Psychological Measurement, 1982</p><p class="ds-related-work--abstract ds2-5-body-sm">This monte carlo study assessed the accuracy of simultaneous estimation of item and person parameters in item response theory. Item responses were simulated using the two-and three-parameter logistic models. Samples of 200, 500, 1,000, and 2,000 simulated examinees and tests of 15, 30, and 60 items were generated. Item and person parameters were then estimated using the appropriate model. The root mean squared error between recovered and actual item characteristic curves served as the principal measure of estimation accuracy for items. The accuracy of estimates of ability was as-</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Recovery of Two and Three-Parameter Logistic Item Characteristic Curves: A Monte Carlo Study","attachmentId":48915886,"attachmentType":"pdf","work_url":"https://www.academia.edu/6327078/Recovery_of_Two_and_Three_Parameter_Logistic_Item_Characteristic_Curves_A_Monte_Carlo_Study","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/6327078/Recovery_of_Two_and_Three_Parameter_Logistic_Item_Characteristic_Curves_A_Monte_Carlo_Study"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="14217354" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/14217354/An_Item_Response_Theory_Modeling_of_Alcohol_and_Marijuana_Dependences_A_National_Drug_Abuse_Treatment_Clinical_Trials_Network_Study">An Item Response Theory Modeling of Alcohol and Marijuana Dependences: A National Drug Abuse Treatment Clinical Trials Network Study</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="33202280" href="https://dukemedschool.academia.edu/DanBlazer">Dan Blazer</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Studies on Alcohol and Drugs, 2009</p><p class="ds-related-work--abstract ds2-5-body-sm">Objective: The aim of this study was to examine psychometric properties of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), diagnostics criteria for alcohol and marijuana dependences among 462 alcohol users and 311 marijuana users enrolled in two multisite trials of the National Drug Abuse Treatment Clinical Trials Network. Method: Diagnostic questions were assessed by the DSM-IV checklist. Data were analyzed by the item response theory and the multiple indicators-multiple causes method procedures. Results: Criterion symptoms of alcohol and marijuana dependences exhibited a high level of internal consistency. All individual symptoms showed good discrimination in distinguishing alcohol or marijuana users between high and low severity levels of the continuum. In both groups, "withdrawal" appeared to measure the most severe symptom of the dependence continuum. There was little evidence of measurement nonequivalence in assessing symptoms of dependence by gender, age, race/ethnicity, and educational level. Conclusions: These findings highlight the clinical utility of the DSM-IV checklist in assessing alcohol-and marijuanadependence syndromes among treatment-seeking substance users. (J.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"An Item Response Theory Modeling of Alcohol and Marijuana Dependences: A National Drug Abuse Treatment Clinical Trials Network Study","attachmentId":44454266,"attachmentType":"pdf","work_url":"https://www.academia.edu/14217354/An_Item_Response_Theory_Modeling_of_Alcohol_and_Marijuana_Dependences_A_National_Drug_Abuse_Treatment_Clinical_Trials_Network_Study","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/14217354/An_Item_Response_Theory_Modeling_of_Alcohol_and_Marijuana_Dependences_A_National_Drug_Abuse_Treatment_Clinical_Trials_Network_Study"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="112370146" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/112370146/418_JOURNAL_OF_STUDIES_ON_ALCOHOL_AND_DRUGS_MAY_2010_An_Item_Response_Theory_Analysis_of_DSM_IV_Alcohol_Use_Disorder_Criteria_and_Binge_Drinking_in_Undergraduates_">418 JOURNAL OF STUDIES ON ALCOHOL AND DRUGS / MAY 2010 An Item-Response Theory Analysis of DSM-IV Alcohol-Use Disorder Criteria and “Binge ” Drinking in Undergraduates*</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="278386046" href="https://independent.academia.edu/BeselerC">Cheryl Beseler</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2015</p><p class="ds-related-work--abstract ds2-5-body-sm">ABSTRACT. Objective: This is the first study to examine the Di-agnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), criteria for alcohol-use disorders and heavy episodic (or “binge”) drinking in a college sample using item-response theory (IRT) analysis. IRT facilitates assessment of the severity of the criteria, their ability to distinguish between those at greatest and lowest risk, and the value of adding a “binge ” drinking criterion. Method: In a sample of undergraduate drinkers (n = 353), we conducted factor analyses to deter-mine whether the criteria best fit a one- or two-factor structure. We then conducted IRT analyses to obtain item-characteristic curves indicating the probability of endorsing a criterion at increasing levels of alcohol-use-disorder risk. These analyses were first conducted including current (i.e., past-year) DSM-IV alcohol-use-disorder criteria only and then rerun adding weekly “binge ” drinking. Results: A single-factor model of t...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"418 JOURNAL OF STUDIES ON ALCOHOL AND DRUGS / MAY 2010 An Item-Response Theory Analysis of DSM-IV Alcohol-Use Disorder Criteria and “Binge ” Drinking in Undergraduates*","attachmentId":109622069,"attachmentType":"pdf","work_url":"https://www.academia.edu/112370146/418_JOURNAL_OF_STUDIES_ON_ALCOHOL_AND_DRUGS_MAY_2010_An_Item_Response_Theory_Analysis_of_DSM_IV_Alcohol_Use_Disorder_Criteria_and_Binge_Drinking_in_Undergraduates_","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/112370146/418_JOURNAL_OF_STUDIES_ON_ALCOHOL_AND_DRUGS_MAY_2010_An_Item_Response_Theory_Analysis_of_DSM_IV_Alcohol_Use_Disorder_Criteria_and_Binge_Drinking_in_Undergraduates_"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":113199508,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":113199508,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_113199508" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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