AI Article Synopsis
- - The R package offers innovative methods to tackle biases and confounding factors in observational studies that compare different treatments or exposures.
- - It is mainly aimed at researchers in medicine and life sciences, but can also be applied in other areas with complex outcomes involving multiple confounding variables.
- - The package includes non-parametric bias correction techniques for survival analysis and enables personalized predictions of treatment outcomes and varying treatment effects across different patient groups.
Article Abstract
The R package implements novel approaches to address biases and confounding when comparing treatments or exposures in observational studies of outcomes. While designed and appropriate for use in comparative safety and effectiveness research involving medicine and the life sciences, the package can be used in other situations involving outcomes with multiple confounders. is an open-source tool for researchers whose aim is to generate high quality evidence using observational data. The package implements a family of methods for non-parametric bias correction when comparing treatments in observational studies, including survival analysis settings, where competing risks and/or censoring may be present. The approach extends to bias-corrected personalized predictions of treatment outcome differences, and analysis of heterogeneity of treatment effect-sizes across patient subgroups.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8330612 | PMC |
| http://dx.doi.org/10.18637/jss.v096.i04 | DOI Listing |
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