Design, analysis, power, and sample size calculation for three-phase interrupted time series analysis in evaluation of health policy interventions
Authors
Zhang, BoLiu, Wei
Lemon, Stephenie C.
Barton, Bruce A.
Fischer, Melissa A.
Lawrence, Colleen
Rahn, Elizabeth J.
Danila, Maria I.
Saag, Kenneth G.
Harris, Paul A.
Allison, Jeroan J.
UMass Chan Affiliations
Prevention Research CenterMeyers Primary Care Institute
Department of Medicine
Department of Population and Quantitative Health Sciences
Document Type
Journal ArticlePublication Date
2019-08-19Keywords
interrupted time seriespolicy evaluation
power
quasi-experimental design
sample size calculation
segmented regression
UMCCTS funding
Biostatistics
Health Policy
Health Services Administration
Health Services Research
Investigative Techniques
Statistics and Probability
Metadata
Show full item recordAbstract
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 -0.9 to 0.9 with various effect sizes. The power increased as the sample size or the effect size increased. The power to detect the same effect sizes varied largely, depending on testing level change, trend changes, or both. CONCLUSION: This article provides a convenient tool for investigators to generate sample sizes to ensure sufficient statistical power when three-phase ITS study design is implemented.Source
J Eval Clin Pract. 2019 Aug 19. doi: 10.1111/jep.13266. [Epub ahead of print] Link to article on publisher's site
DOI
10.1111/jep.13266Permanent Link to this Item
http://hdl.handle.net/20.500.14038/46823PubMed ID
31429175Related Resources
ae974a485f413a2113503eed53cd6c53
10.1111/jep.13266