Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic
Ontology highlight
ABSTRACT: Mediation analysis draws increasing attention in many research areas such as economics, finance and social sciences. In this paper, we propose new statistical inference procedures for high dimensional mediation models, in which both the outcome model and the mediator model are linear with high dimensional mediators. Traditional procedures for mediation analysis cannot be used to make statistical inference for high dimensional linear mediation models due to high-dimensionality of the mediators. We propose an estimation procedure for the indirect effects of the models via a partially penalized least squares method, and further establish its theoretical properties. We further develop a partially penalized Wald test on the indirect effects, and prove that the proposed test has a
SUBMITTER: Guo X
PROVIDER: S-EPMC9759674 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
ACCESS DATA