Interrupted time series (ITS) analysis is a valuable study design for evaluating the
effectiveness of population-level health interventions that have been implemented at a …

The wide variety of dissemination and implementation designs now being used to evaluate
and improve health systems and outcomes warrants review of the scope, features, and …

Background COVID‐19 school closures pose a threat to children's wellbeing, but no COVID‐
19‐related studies have assessed children's behaviours over multiple years. Objective To …

This work investigates whether and how COVID-19 containment policies had an immediate
impact on crime trends in Los Angeles. The analysis is conducted using Bayesian structural …

Interrupted time series analysis differs from most other intervention study designs in that it
involves a before-after comparison within a single population, rather than a comparison with …

In this article, I introduce the itsa command, which performs interrupted time-series analysis
for single-and multiple-group comparisons. In an interrupted time-series analysis, an …

Recognition of the benefits to trauma-informed approaches is expanding, along with
commensurate interest in extending delivery within school systems. Although information …

Interrupted time series (ITS) analysis is arguably the strongest quasi-experimental research
design. ITS is particularly useful when a randomized trial is infeasible or unethical. The …

Featuring engaging examples from diverse disciplines, this book explains how to use
modern approaches to quasi-experimentation to derive credible estimates of treatment …

This book provides a comprehensive introduction to latent variable growth curve modeling
(LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its …