Identification of an additive interaction using parameter regularization and model selection in epidemiology.

ABSTRACT:

Background

In epidemiology, indicators such as the relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (S) are commonly used to assess additive interactions between two variables. However, the results of these indicators are sometimes inconsistent in real world applications and it may be difficult to draw conclusions from them.

Method

Based on the relationship between the RERI, AP, and S, we propose a method with consistent results, which are achieved by constraining eθ3-eθ1-eθ2+1=0 , and the interpretation of the results is simple and clear. We present two pathways to achieve this end: one is to complete the constraint by adding a regular penalty term to the model likelihood function; the other is to use model selection.

Result

SUBMITTER: Hu C 

PROVIDER: S-EPMC11485060 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature