Discussion: Efficiency and Self‐efficiency With Multiple Imputation Inference

Publisher Website
Google Scholar
Abstract
Summary: By closely examining the examples provided in Nielsen (2003), this paper further explores the relationship between self‐efficiency (Meng, 1994) and the validity of Rubin's multiple imputation (RMI) variance combining rule. The RMI variance combining rule is based on the common assumption/intuition that the efficiency of our estimators decreases when we have less data. However, there are estimation procedures that will do the opposite, that is, they can produce more efficient estimators with less data. Self‐efficiency is a theoretical formulation for excluding such procedures. When a user, typically unaware of the hidden self‐inefficiency of his choice, adopts a self‐inefficient complete‐data estimation procedure to conduct an RMI inference, the theoretical validity of his inference becomes a complex issue, as we demonstrate. We also propose a diagnostic tool for assessing potential self‐inefficiency and the bias in the RMI variance estimator, at the outset of RMI inference, by constructing a convenient proxy to the RMI point estimator.

This publication has 0 references indexed in Scilit: