Can auxiliary variables be used in research on aging and the life course?

Aug 27, 2024 ... Auxiliary variables are used in multiple imputation (MI) to reduce bias and increase efficiency. These variables may often themselves be ... Apr 17, 2018 ... I have three ordinal variables relating to public spending preferences that are all strongly correlated. One of them is missing around a 103 observations, ... Layer-Parallel Training of Residual Networks with Auxiliary-Variable Networks. 10 Dec 2021 · Qi Sun, Hexin Dong, Zewei Chen, Jiacheng Sun, Zhenguo Li, Bin ... We stipulate a new structural rule for adjusting auxiliary variables when strengthening preconditions and weakening postconditions. Courtesy of this new rule, ... Feb 14, 2025 ... Abstract. We present a novel optimization algorithm, a relaxed vector auxiliary variable (RVAV), that satisfies an unconditional energy ... Jul 11, 2024 ... A way to evolve this auxiliary state without having it get integrated along with the ODE state. Adding this feature would likely come with some practical and ... Abstract. We present a new approach to sample from generic binary distributions, based on an exact Hamiltonian Monte Carlo algorithm applied to a piecewise ... We consider data as in Figure 1, where X1 is an auxiliary variable measured with error for all n sampled individuals, X2 is the underlying true value of X1, ... 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 ... Apr 23, 2018 ... The current study provides an overview of systematic approaches that allows researchers to investigate models involving moderation, conditional effects on ...