Package: EHRmuse 0.0.2.2

EHRmuse: Multi-Cohort Selection Bias Correction using IPW and AIPW Methods

Comprehensive toolkit for addressing selection bias in binary disease models across diverse non-probability samples, each with unique selection mechanisms. It utilizes Inverse Probability Weighting (IPW) and Augmented Inverse Probability Weighting (AIPW) methods to reduce selection bias effectively in multiple non-probability cohorts by integrating data from either individual-level or summary-level external sources. The package also provides a variety of variance estimation techniques. Please refer to Kundu et al. <doi:10.48550/arXiv.2412.00228>.

Authors:Ritoban Kundu [aut], Michael Kleinsasser [cre]