Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA
Research Article
Evaluating Reproducibility and Generalizability of a Medical Predictive Model in Clinical Research
Author(s): Fengnan Li* and Shein Chung Chow
In clinical research, a medical predictive model is intended to provide insight into the impact of risk factors (predictors) such as demographics
and patient characteristics on clinical outcomes. A validated medical predictive model informs disease status and treatment effects under study.
More importantly, it can be used for disease management. However, a gap in the development process of these models is often observed. That
is, most studies only focus on the internal validation for the model's reproducibility but overlook the external validation needed for evaluating
generalizability. To solve this issue, this article proposes several methods for assessing both the reproducibility and generalizability of a developed/
validated medical predictive model. The generalizability estimation approaches allow for sensitivity analysis in situations where data on new
po.. Read More»
DOI:
10.37421/2155-6180.2024.15.212
Journal of Biometrics & Biostatistics received 3254 citations as per Google Scholar report