Analysis of semiparametric regression models for repeated outcomes in the presence of missing data

By James M. Robins, Andrea Rotnitzky, Lue Ping Zhao. 1995

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In Statistics and Probability

Citations in the corpus

Double/De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers (2018, background): “Doubly robust estimating equations as in Robins et al. (1995) and Robins and Rotnitzky (1995) have this structure.”
Approximate residual balancing: debiased inference of average treatment effects in high dimensions (2016, background): “Moreover, lim sup n→∞ nc‖γ‖22 ρ−2E [{ e.Xi/ 1− e.Xi/ }2 ∣∣∣∣Wi=0 ] : .19/ The rate of convergence that is guaranteed by expression (19) is the same as what we would obtain if we actually knew the true propensities and could use them for weighting (Robins et al., 1994, 1995).”
Efficient Policy Learning (2017, background): “Given unconfoundedness (3), there is a large literature that develops a semiparametric efficient estimation theory for statistics like Q(π) (Bickel et al., 1998; Hahn, 1998; Hirano et al., 2003; Robins and Rotnitzky, 1995; Robins et al., 1995), for any fixed policy π.”
Skill Transferability, Migration, and Development: Evidence from Population Resettlement in Indonesia (2016, methodology): “This double robust specification (Robins et al., 1995) augments the usual inverse probability weighting (IPW) specification by controlling for the underlying terms used to estimate propensity scores.”
An Introduction to Generalized Estimating Equations and an Application to Assess Selectivity Effects in a Longitudinal Study on Very Old Individuals (2004, background): “In particular, Robins, Rotnitzky, and Zhao (1995) propose an extension of GEEs for data that are MAR (several approaches to identify the type of dropout have been suggested, e.g., Diggle et al., 2002; Qu & Song, 2002).”
What is China's true unemployment rate? (2005, background): “8 Robins, Rotnitzky, and Zhao (1995), first showed how an IPW estimator could be used to estimate conditional means in the presence of attrition in panel data.”
Causal Inference With General Treatment Regimes (2004, methodology): “Our criticism of the ignorability assumption is substantive in nature; Rosenbaum and Rubin (1983a) described a method for quantifying the sensitivity of results to Assumption 2.”