EHRmuse
Multi-Cohort Selection Bias Correction using IPW and AIPW Methods
v0.0.2.2
·
Jul 8, 2025
·
GPL (>= 2)
Description
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>.
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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
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0.0.2.2
Mar 9, 2026