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      Designing a stepped wedge trial: three main designs, carry-over effects and randomisation approaches

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          Abstract

          Background There is limited guidance on the design of stepped wedge cluster randomised trials. Current methodological literature focuses mainly on trials with cross-sectional data collection at discrete times, yet many recent stepped wedge trials do not follow this design. In this article, we present a typology to characterise the full range of stepped wedge designs, and offer guidance on several other design aspects. Methods We developed a framework to define and report the key characteristics of a stepped wedge trial, including cluster allocation and individual participation. We also considered the relative strengths and weaknesses of trials according to this framework. We classified recently published stepped wedge trials using this framework and identified illustrative case studies. We identified key design choices and developed guidance for each. Results We identified three main stepped wedge designs: those with a closed cohort, an open cohort, and a continuous recruitment short exposure design. In the first two designs, many individuals experience both control and intervention conditions. In the final design, individuals are recruited in continuous time as they become eligible and experience either the control or intervention condition, but not both, and then provide an outcome measurement at follow-up. While most stepped wedge trials use simple randomisation, stratification and restricted randomisation are often feasible and may be useful. Some recent studies collect outcome information from individuals exposed a long time before or after the rollout period, but this contributes little to the primary analysis. Incomplete designs should be considered when the intervention cannot be implemented quickly. Carry-over effects can arise in stepped wedge trials with closed and open cohorts. Conclusions Stepped wedge trial designs should be reported more clearly. Researchers should consider the use of stratified and/or restricted randomisation. Trials should generally not commit resources to collect outcome data from individuals exposed a long time before or after the rollout period. Though substantial carry-over effects are uncommon in stepped wedge trials, researchers should consider their possibility before conducting a trial with closed or open cohorts.

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          Design and analysis of stepped wedge cluster randomized trials.

          Cluster randomized trials (CRT) are often used to evaluate therapies or interventions in situations where individual randomization is not possible or not desirable for logistic, financial or ethical reasons. While a significant and rapidly growing body of literature exists on CRTs utilizing a "parallel" design (i.e. I clusters randomized to each treatment), only a few examples of CRTs using crossover designs have been described. In this article we discuss the design and analysis of a particular type of crossover CRT - the stepped wedge - and provide an example of its use.
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            The stepped wedge cluster randomised trial: rationale, design, analysis, and reporting

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              Stepped wedge designs could reduce the required sample size in cluster randomized trials.

              The stepped wedge design is increasingly being used in cluster randomized trials (CRTs). However, there is not much information available about the design and analysis strategies for these kinds of trials. Approaches to sample size and power calculations have been provided, but a simple sample size formula is lacking. Therefore, our aim is to provide a sample size formula for cluster randomized stepped wedge designs. We derived a design effect (sample size correction factor) that can be used to estimate the required sample size for stepped wedge designs. Furthermore, we compared the required sample size for the stepped wedge design with a parallel group and analysis of covariance (ANCOVA) design. Our formula corrects for clustering as well as for the design. Apart from the cluster size and intracluster correlation, the design effect depends on choices of the number of steps, the number of baseline measurements, and the number of measurements between steps. The stepped wedge design requires a substantial smaller sample size than a parallel group and ANCOVA design. For CRTs, the stepped wedge design is far more efficient than the parallel group and ANCOVA design in terms of sample size. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Trials
                Trials
                Springer Science and Business Media LLC
                1745-6215
                December 2015
                August 17 2015
                December 2015
                : 16
                : 1
                Article
                10.1186/s13063-015-0842-7
                cd18feb4-caf4-43de-8fb9-6141b253eee2
                © 2015

                http://creativecommons.org/licenses/by/4.0

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