Statistical Methods for Development, Validation, and Implementation of Absolute Risk Models [Methods Study], 2016-2022 (ICPSR 39730)
Factors, such as personal traits, behaviors, or the environment, can affect a person's risk of getting an illness. Doctors can use risk models, which account for these factors, to predict a person's chance of getting an illness. The risk models group patients into different levels for certain illnesses, such as high risk or low risk.
Most risk models look at only a small number of factors, which affects how well the models can separate patients into different levels. Combining factors from different studies into a single risk model may improve how well the model works. Researchers can use statistical methods to combine data from different studies. But current methods don't work when the studies look at different traits or other factors.
In this study, the research team developed a new method for combining data from studies that have information on different risk factors. The new method is called Generalized Meta-Analysis, or GENMETA.
To access the R package, please visit the Implements Generalized Meta-Analysis Using Iterated Reweighted Least Square Algorithm CRAN webpage.