Patient feasibility as a novel approach for integrating IRT and LCA statistical models into patient-centric qualitative data—a pilot study
LCA identified three latent classes each with distinct characteristics pertaining to a latent trait defined as patient feasibility. Covariate analyses further highlighted subgroup behaviors. In addition, IRT analyses using the two-parameter logistic model, generalized partial credit model, and nominal response model highlighted further distinct characteristics of the studied group. The results provided insights into perceived treatment challenges, logistic challenges, and limiting factors regarding the standard of care therapy and clinical trial attitudes.
Authors
- Matthias Klüglich
- Bert Santy
- Mihail Tanev
- Kristian Hristov
- Tsveta Mincheva
Institutions
- Boehringer Ingelheim (Germany) (DE)
- Finmeccanica (United Kingdom) (GB)
- Boehringer Ingelheim (Egypt) (EG)
- Boehringer Ingelheim (Belgium) (BE)
- Boehringer Ingelheim (South Korea) (KR)
Publication Details
- Journal
- Frontiers in Digital Health
- Published
- 2024-10-02
- DOI
- https://doi.org/10.3389/fdgth.2024.1378497
- Primary Topic
- Advanced Statistical Modeling Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00