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Peer-reviewed

Design, analysis, power, and sample size calculation for three‐phase interrupted time series analysis in evaluation of health policy interventions

Bo Zhang, Wei Liu, Stephenie C. Lemon, Bruce Barton, Melissa A. Fischer, Colleen Lawrence, Elizabeth J. Rahn, Maria I. Danila, Kenneth G. Saag, Paul A. Harris, Jeroan J. Allison

Journal of Evaluation in Clinical Practice · 2019

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Summary

OBJECTIVE: To discuss the study design and data analysis for three-phase interrupted time series (ITS) studies to evaluate the impact of health policy, systems, or environmental interventions. Simulation methods are used to conduct power and sample size calculation for these studies. METHODS: We consider the design and analysis of three-phase ITS studies using a study funded by National Institutes of Health as an exemplar. The design and analysis of both one-arm and two-arm three-phase ITS studies are introduced. RESULTS: A simulation-based approach, with ready-to-use computer programs, was developed to determine the power for two types of three-phase ITS studies. Simulations were conducted to estimate the power of segmented autoregressive (AR) error models when autocorrelation ranged from

Subject
Other / interdisciplinary
Source type
Peer-reviewed study
System type
Other
DOI
10.1111/jep.13266
Catalogue ID
BFmou2m1rn-9ygin0
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