Sparse Extended Redundancy Analysis: Variable Selection via the Exclusive LASSO.

Extended Redundancy Analysis is a statistical tool for exploring the directional relationships of multiple sets of exogenous variables on a set of endogenous variables. This approach posits that the endogenous and exogenous variables are related via latent components, each of which is extracted from a set of exogenous variables, that account for the maximum variation of the endogenous variables. However, it is often difficult to distinguish between the true variables that form the latent components and the false variables that do not, especially when the association between the true variables and the exogenous set is weak.

Mobile-Based Interventions for Dietary Behavior Change and Health Outcomes: Scoping Review.

Background: Mobile apps are being widely used for delivering health interventions, with their ubiquitous access and sensing capabilities. One such use is the delivery of interventions for healthy eating behavior.

Objective: The aim of this study was to provide a comprehensive view of the literature on the use of mobile interventions for eating behavior change.