Assessing Alternative Imputation Strategies for Infrequently Missing Items on Multi-item Scales.

ABSTRACT: Health-science researchers often measure psychological constructs using multi-item scales and encounter missing items on some participants. Multiple imputation (MI) has emerged as an alternative to ad-hoc methods (e.g., mean substitution) for handling incomplete data on multi-item scales, appealingly reflecting available information while accounting for uncertainty due to missing values in a unified inferential framework. However, MI can be implemented in a variety of ways. When the number of variables to impute gets large, some strategies yield unstable estimates of quantities of interest while others are not technically feasible to implement. These considerations raise pragmatic questions about the extent to which ad-hoc procedures would yield statistical properties that ar

SUBMITTER: Rezvan PH 

PROVIDER: S-EPMC9718541 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature