Doubly robust inference with missing data in survey sampling

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Doubly Robust Inference With Nonprobability Survey Samples (2018, methodology): “The doubly robust variance estimation technique proposed by Kim and Haziza (2014) is a preferred approach and can be implemented under the current context.”
Model-assisted inference for treatment effects using regularized calibrated estimation with high-dimensional data (2018, methodology): “Conditions (23)–(24) were previously used by Kim and Haziza (2014) and Vermeulen and Vansteelandt (2015) to construct an augmented IPW estimator μ̂1(m̂1, π̂) for μ1 in low-dimensional settings, where (α̂1, γ̂ ) are nonpenalized, defined by directly setting (31)–(32) to zero.”