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Supervised Multidimensional Item Response Theory Modeling of Pediatric Iatrogenic Withdrawal Symptoms
Item‐level data from composite scales can be analyzed with pharmacometric item response theory (IRT) models to improve the quantification of disease severity compared with the use of total composite scores. However, regular IRT models assume unidimensionality, which is violated in the scale measurin...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6930857/ https://www.ncbi.nlm.nih.gov/pubmed/31612647 http://dx.doi.org/10.1002/psp4.12469 |
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author | Goulooze, Sebastiaan C. Ista, Erwin van Dijk, Monique Hankemeier, Thomas Tibboel, Dick Knibbe, Catherijne A.J. Krekels, Elke H.J. |
author_facet | Goulooze, Sebastiaan C. Ista, Erwin van Dijk, Monique Hankemeier, Thomas Tibboel, Dick Knibbe, Catherijne A.J. Krekels, Elke H.J. |
author_sort | Goulooze, Sebastiaan C. |
collection | PubMed |
description | Item‐level data from composite scales can be analyzed with pharmacometric item response theory (IRT) models to improve the quantification of disease severity compared with the use of total composite scores. However, regular IRT models assume unidimensionality, which is violated in the scale measuring iatrogenic withdrawal in children because some items are also affected by pain, undersedation, or delirium. Here, we compare regular IRT modelling of pediatric iatrogenic withdrawal symptom data with two new analysis approaches in which the latent variable is guided towards the condition of interest using numerical withdrawal severity scored by nurses as a “supervising variable:” supervised IRT (sIRT) and supervised multi‐dimensional (smIRT) modelling. In this example, in which the items scores are affected by multiple conditions, regular IRT modeling is worse to quantify disease severity than the total composite score, whereas improved performance compared with the composite score is observed for the sIRT and smIRT models. |
format | Online Article Text |
id | pubmed-6930857 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-69308572019-12-27 Supervised Multidimensional Item Response Theory Modeling of Pediatric Iatrogenic Withdrawal Symptoms Goulooze, Sebastiaan C. Ista, Erwin van Dijk, Monique Hankemeier, Thomas Tibboel, Dick Knibbe, Catherijne A.J. Krekels, Elke H.J. CPT Pharmacometrics Syst Pharmacol Research Item‐level data from composite scales can be analyzed with pharmacometric item response theory (IRT) models to improve the quantification of disease severity compared with the use of total composite scores. However, regular IRT models assume unidimensionality, which is violated in the scale measuring iatrogenic withdrawal in children because some items are also affected by pain, undersedation, or delirium. Here, we compare regular IRT modelling of pediatric iatrogenic withdrawal symptom data with two new analysis approaches in which the latent variable is guided towards the condition of interest using numerical withdrawal severity scored by nurses as a “supervising variable:” supervised IRT (sIRT) and supervised multi‐dimensional (smIRT) modelling. In this example, in which the items scores are affected by multiple conditions, regular IRT modeling is worse to quantify disease severity than the total composite score, whereas improved performance compared with the composite score is observed for the sIRT and smIRT models. John Wiley and Sons Inc. 2019-10-15 2019-12 /pmc/articles/PMC6930857/ /pubmed/31612647 http://dx.doi.org/10.1002/psp4.12469 Text en © 2019 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of the American Society for Clinical Pharmacology and Therapeutics. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Goulooze, Sebastiaan C. Ista, Erwin van Dijk, Monique Hankemeier, Thomas Tibboel, Dick Knibbe, Catherijne A.J. Krekels, Elke H.J. Supervised Multidimensional Item Response Theory Modeling of Pediatric Iatrogenic Withdrawal Symptoms |
title | Supervised Multidimensional Item Response Theory Modeling of Pediatric Iatrogenic Withdrawal Symptoms |
title_full | Supervised Multidimensional Item Response Theory Modeling of Pediatric Iatrogenic Withdrawal Symptoms |
title_fullStr | Supervised Multidimensional Item Response Theory Modeling of Pediatric Iatrogenic Withdrawal Symptoms |
title_full_unstemmed | Supervised Multidimensional Item Response Theory Modeling of Pediatric Iatrogenic Withdrawal Symptoms |
title_short | Supervised Multidimensional Item Response Theory Modeling of Pediatric Iatrogenic Withdrawal Symptoms |
title_sort | supervised multidimensional item response theory modeling of pediatric iatrogenic withdrawal symptoms |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6930857/ https://www.ncbi.nlm.nih.gov/pubmed/31612647 http://dx.doi.org/10.1002/psp4.12469 |
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