Improving prediction of eating-related behavioral outcomes with zero-sensitive regression models.

ABSTRACT:

Objective

Outcome variables gauging the frequency of specific disordered eating behaviors (e.g., binge eating, vomiting) are common in the study of eating and health behaviors. The nature of such data presents several analytical challenges, which may be best addressed through the application of underutilized statistical approaches. While zero-sensitive models are well-supported by methodologists, application of these models has yet to gain traction among a widespread audience of researchers who study eating-related behaviors. The current study examined several approaches to predicting count-based behaviors, including zero-sensitive (i.e., zero-inflated and hurdle) regression models.

Method

Exploration of alternative models to predict eating-related behaviors occurred in two

SUBMITTER: Schaumberg K 

PROVIDER: S-EPMC6778476 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature