Using a monotone single-index model to stabilize the propensity score in missing data problems and causal inference
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Publication:6625962
DOI10.1002/sim.8048zbMATH Open1545.62509WikidataQ64119515 ScholiaQ64119515MaRDI QIDQ6625962
Jing Qin, Baojiang Chen, Tao Yu, Pengfei Li, Hao Liu
Publication date: 28 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
empirical processmissing datacausal inferencesingle-index modelpool adjacent violation algorithminverse weighting
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Related Items (3)
A calibration method to stabilize estimation with missing data ⋮ Kernel density estimation in mixture models with known mixture proportions ⋮ Using a monotonic density ratio model to increase the power of the goodness-of-fit test for logistic regression models with case-control data
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