Literature DB >> 24108271

Item response theory and structural equation modelling for ordinal data: Describing the relationship between KIDSCREEN and Life-H.

Andrew C Titman1, Gillian A Lancaster2, Allan F Colver3.   

Abstract

Both item response theory and structural equation models are useful in the analysis of ordered categorical responses from health assessment questionnaires. We highlight the advantages and disadvantages of the item response theory and structural equation modelling approaches to modelling ordinal data, from within a community health setting. Using data from the SPARCLE project focussing on children with cerebral palsy, this paper investigates the relationship between two ordinal rating scales, the KIDSCREEN, which measures quality-of-life, and Life-H, which measures participation. Practical issues relating to fitting models, such as non-positive definite observed or fitted correlation matrices, and approaches to assessing model fit are discussed. item response theory models allow properties such as the conditional independence of particular domains of a measurement instrument to be assessed. When, as with the SPARCLE data, the latent traits are multidimensional, structural equation models generally provide a much more convenient modelling framework.
© The Author(s) 2013.

Entities:  

Keywords:  cerebral palsy; health assessment; item response theory; ordinal data; structural equation modelling

Mesh:

Year:  2013        PMID: 24108271     DOI: 10.1177/0962280213504177

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  3 in total

1.  Translation of questionnaires measuring health related quality of life is not standardized: a literature based research study.

Authors:  Anne Kjaergaard Danielsen; Hans-Christian Pommergaard; Jakob Burcharth; Eva Angenete; Jacob Rosenberg
Journal:  PLoS One       Date:  2015-05-12       Impact factor: 3.240

2.  Systematic Review of Cerebral Palsy Registries/Surveillance Groups: Relationships between Registry Characteristics and Knowledge Dissemination.

Authors:  Donna S Hurley; Theresa Sukal-Moulton; Deborah Gaebler-Spira; Kristin J Krosschell; Larissa Pavone; Akmer Mutlu; Julius Pa Dewald; Michael E Msall
Journal:  Int J Phys Med Rehabil       Date:  2015-03-23

Review 3.  Item response models for the longitudinal analysis of health-related quality of life in cancer clinical trials.

Authors:  Antoine Barbieri; Jean Peyhardi; Thierry Conroy; Sophie Gourgou; Christian Lavergne; Caroline Mollevi
Journal:  BMC Med Res Methodol       Date:  2017-09-26       Impact factor: 4.615

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.