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Power and sample size determination for stepped wedge cluster randomized trials

Keener, Christopher (2018) Power and sample size determination for stepped wedge cluster randomized trials. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

A stepped wedge trial is a type of cluster randomized trial with unidirectional crossover from control to intervention. In this study, we classified stepped wedge trial designs according to subject recruitment and outcome exposure. Based upon those criteria, we proposed three types of classification, that is, fixed cohort (baseline recruitment with longitudinal exposure), expanding cohort (continuous recruitment with longitudinal exposure), and cross-sectional (continuous recruitment with cross-sectional exposure). For each design type, we proposed a corresponding model for estimating treatment effect. We conducted Monte Carlo simulations to study the impact of design and analytic assumptions on the sample size and power determination. These assumptions include homogeneous or heterogeneous temporal effects between clusters, fixed or time-varying treatment effect, modeling temporal trend through or not through step effects, and choice of correlation structure. To investigate how these assumptions were made in the published trials, we conducted a systematic review of 300 stepped wedge trials published up to 2017. From the review we found that more than one fourth of these trials did not make it clear in their reports about the type, the assumptions, or models in estimating treatment effect and sample size calculations. The majority of the trials did not mention the methods for handling missing data. This suggests the need for developing standards of reporting stepped wedge trials like CONSORT for randomized trials or STROBE for observational studies.
PUBLIC HEALTH SIGNIFICANCE: Stepped wedge trials are popular for evaluating community-based interventions in public health. This research has focused on three areas of improving the design of a stepped wedge trial: classification of key design aspects, power and sample size determination, and modeling method for estimation and inference the effect of an intervention. Sample size determination is important to ensure that the trial is adequately powered. Model misspecification and incorrect analytic assumption both can lead to inflated Type I error rate or an underpowered trial. Our systematic review found that many stepped wedge trials failed to define key aspects and assumptions of their designs when publishing. Thus, use of our classification of stepped wedge trials will improve technical communication on trials commonly used for public health research.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Keener, Christophercmk93@pitt,educmk93
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorChang, Chung Chouchangj@pitt.eduCHANGJ
Committee MemberYouk, Adaayouk@pitt.eduayouk
Committee MemberKellum, Johnkellum@pitt.edukellum
Committee MemberJeong, Jongjjeong@pitt.edujjeong
Committee MemberJesse, Hsujesse.hsu@pennmedicine.upenn.edun/a
Date: 26 September 2018
Date Type: Publication
Defense Date: 18 July 2018
Approval Date: 26 September 2018
Submission Date: 23 July 2018
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 128
Institution: University of Pittsburgh
Schools and Programs: Graduate School of Public Health > Biostatistics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: cluster randomized trials, Monte Carlo simulation, power, sample size, stepped wedge trial, systematic review
Date Deposited: 26 Sep 2018 14:08
Last Modified: 26 Sep 2018 14:08
URI: http://d-scholarship.pitt.edu/id/eprint/35034

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