Interpretation of coefficients in segmented regression for interrupted time series analyses.

ABSTRACT:

Background

Segmented regression, a common model for interrupted time series (ITS) analysis, primarily utilizes two equation parametrizations. Interpretations of coefficients vary between the two segmented regression parametrizations, leading to occasional user misinterpretations.

Methods

To illustrate differences in coefficient interpretation between two common parametrizations of segmented regression in ITS analysis, we derived analytical results and present an illustration evaluating the impact of a smoking regulation policy in Italy using a publicly accessible dataset. Estimated coefficients and their standard errors were obtained using two commonly used parametrizations for segmented regression with continuous outcomes. We clarified coefficient interpretations and interv

SUBMITTER: Wang Y 

PROVIDER: S-EPMC12001611 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature