Open AccessModeling Composite Assessment Data Using Item Response Theory
Author(s) -
Ueckert Sebastian
Publication year - 2018
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1002/psp4.12280
Subject(s) - item response theory , computer science , context (archaeology) , variety (cybernetics) , data type , data science , data mining , machine learning , artificial intelligence , statistics , mathematics , psychometrics , programming language , paleontology , biology
Composite assessments aim to combine different aspects of a disease in a single score and are utilized in a variety of therapeutic areas. The data arising from these evaluations are inherently discrete with distinct statistical properties. This tutorial presents the framework of the item response theory (IRT) for the analysis of this data type in a pharmacometric context. The article considers both conceptual (terms and assumptions) and practical questions (modeling software, data requirements, and model building).