By modeling the observed outcome with a location-scale model and fitting an induced logistic regression for missingness, the proposed estimator avoids the multiple-root instability of inverse probability weighting for non-ignorable missing data.
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Instability of inverse probability weighting methods and a remedy for non-ignorable missing data
By modeling the observed outcome with a location-scale model and fitting an induced logistic regression for missingness, the proposed estimator avoids the multiple-root instability of inverse probability weighting for non-ignorable missing data.