Beard, Emma;
Brown, Jamie;
Shahab, Lion;
(2025)
Sample size requirements to evaluate policies in addiction research using interrupted time series analysis (ITS): Tools and guidance.
Addiction
10.1111/add.70220.
(In press).
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Abstract
Formal power calculations are rarely presented in interrupted time-series (ITS) studies due to their technical complexity, creating a significant gap in methodological rigor. This paper aimed to make power and sample size determination more accessible for researchers, particularly in the field of addiction, by providing a suite of practical and user-friendly tools. A set of resources was developed using Monte Carlo simulation to allow researchers to estimate statistical power under a wide range of ITS design parameters. The approach allows for the explicit definition of the data-generating process, including specific autocorrelation error structures (ARMA), the presence of covariates and trends and different intervention effect types (step, pulse and trend change). The study produced three key resources: (1) a flexible R code base for conducting custom power simulations, (2) an intuitive, interactive R Shiny App that enables code-free power analysis through a web interface and (3) a series of pre-calculated look-up tables for quick sample size estimation during the initial stages of study design. Illustrative examples from addiction research demonstrate the tools' application. The provided tools bridge a critical gap by simplifying the process of conducting rigorous power calculations for ITS designs. Their adoption can enhance the planning, execution and interpretation of quasi-experimental studies, helping to ensure that research is adequately powered to detect meaningful policy and intervention effects.
| Type: | Article |
|---|---|
| Title: | Sample size requirements to evaluate policies in addiction research using interrupted time series analysis (ITS): Tools and guidance |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/add.70220 |
| Publisher version: | https://doi.org/10.1111/add.70220 |
| Language: | English |
| Additional information: | Copyright © 2025 The Author(s). Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction. This is an open access article under the terms of the Creative Commons Attribution License, https://creativecommons.org/licenses/by/4.0/, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | ARIMA, ITS, policy evaluation, power, sample size, time series |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Behavioural Science and Health |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10215817 |
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