How are auxiliary variables used in doubly robust estimation?

Oct 7, 2020 ... Topic 33: Auxiliary Variables (PETARS, Chapter 5) ... Captions may be available for this content for accessibility purposes. They may not always ... Aug 28, 2020 ... Auxiliary variables (which is created by pyro.sample(name, dist, infer={'is_auxiliary': True}) are used internally in some special cases, which you might be ... This article introduces a novel estimator known as the neutrosophic ratio-cum-product exponential estimator combining two auxiliary variables, specifically ... Nov 10, 2020 ... Title:Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration ... Abstract:Discrete structures play an important role in ... Apr 23, 2018 ... The current study provides an overview of systematic approaches that allows researchers to investigate models involving moderation, conditional effects on ... The data in the auxiliary file is primarily imputed from other datasets including the Medical Expenditure Panel Survey Household Component (MEPS-HC), Medical ... auxiliary variable given a set of other Z variables already in an imputation model, similar to the conditional partial R indicators of Schouten et al. (201 ... Good auxiliary variables can also be correlates or predictors of missingness. Let's create a set of missing data flags for each variable to be imputed. We will ... Whitaker, Salina Wu, "The Combined Impact of Continuous and Ordinal Auxiliary Variables on Missing Data Imputation in SEM" (2021). Electronic Theses and ... The full model outperformed all auxiliary variable selection strategies in the simulation study, with the LASSO strategy the best performing auxiliary variable ...