swdpwr: A SAS Macro and An R Package for Power Calculations in Stepped Wedge Cluster Randomized Trials

2021 ◽  
pp. 106522
Author(s):  
Jiachen Chen ◽  
Xin Zhou ◽  
Fan Li ◽  
Donna Spiegelman
Keyword(s):  
Randomized Trials ◽  
R Package ◽  
Cluster Randomized Trials ◽  
Stepped Wedge ◽  
Power Calculations ◽  
Sas Macro ◽  
Cluster Randomized

Optimal Sample Allocation Under Unequal Costs in Cluster-Randomized Trials

2020 ◽  
Vol 45 (4) ◽  
pp. 446-474
Author(s):  
Zuchao Shen ◽  
Benjamin Kelcey
Keyword(s):  
Optimal Design ◽  
Statistical Power ◽  
Randomized Trials ◽  
Intraclass Correlation ◽  
R Package ◽  
Design Parameters ◽  
Cluster Randomized Trials ◽  
Cost Structures ◽  
Cluster Randomized ◽  
Sample Allocation

Conventional optimal design frameworks consider a narrow range of sampling cost structures that thereby constrict their capacity to identify the most powerful and efficient designs. We relax several constraints of previous optimal design frameworks by allowing for variable sampling costs in cluster-randomized trials. The proposed framework introduces additional design considerations and has the potential to identify designs with more statistical power, even when some parameters are constrained due to immutable practical concerns. The results also suggest that the gains in efficiency introduced through the expanded framework are fairly robust to misspecifications of the expanded cost structure and concomitant design parameters (e.g., intraclass correlation coefficient). The proposed framework is implemented in the R package odr.

scholarly journals Impact of unequal cluster sizes for GEE analyses of stepped wedge cluster randomized trials with binary outcomes

2021 ◽  
Author(s):  
Zibo Tian ◽  
John S. Preisser ◽  
Denise Esserman ◽  
Elizabeth L. Turner ◽  
Paul J. Rathouz ◽  
...  
Keyword(s):  
Randomized Trials ◽  
Binary Outcomes ◽  
Cluster Randomized Trials ◽  
Stepped Wedge ◽  
Cluster Randomized ◽  
Unequal Cluster

scholarly journals Novel methods for the analysis of stepped wedge cluster randomized trials

2019 ◽  
Vol 39 (7) ◽  
pp. 815-844 ◽  
Author(s):  
Lee Kennedy‐Shaffer ◽  
Victor Gruttola ◽  
Marc Lipsitch
Keyword(s):  
Randomized Trials ◽  
Cluster Randomized Trials ◽  
Stepped Wedge ◽  
Novel Methods ◽  
Cluster Randomized

scholarly journals Statistical Properties of Stepped Wedge Cluster-Randomized Trials in Infectious Disease Outbreaks

2020 ◽  
Author(s):  
Lee Kennedy-Shaffer ◽  
Marc Lipsitch
Keyword(s):  
Infectious Disease ◽  
Randomized Trials ◽  
Disease Outbreaks ◽  
Statistical Properties ◽  
Cluster Randomized Trials ◽  
Stepped Wedge ◽  
Infectious Disease Outbreaks ◽  
New Methods ◽  
Stepped Wedge Trials ◽  
Cluster Randomized

ABSTRACTRandomized controlled trials are crucial for the evaluation of interventions such as vaccinations, but the design and analysis of these studies during infectious disease outbreaks is complicated by statistical, ethical, and logistical factors. Attempts to resolve these complexities have led to the proposal of a variety of trial designs, including individual randomization and several types of cluster randomization designs: parallel-arm, ring vaccination, and stepped wedge designs. Because of the strong time trends present in infectious disease incidence, however, methods generally used to analyze stepped wedge trials may not perform well in these settings. Using simulated outbreaks, we evaluate various designs and analysis methods, including recently proposed methods for analyzing stepped wedge trials, to determine the statistical properties of these methods. While new methods for analyzing stepped wedge trials can provide some improvement over previous methods, we find that they still lag behind parallel-arm cluster-randomized trials and individually-randomized trials in achieving adequate power to detect intervention effects. We also find that these methods are highly sensitive to the weighting of effect estimates across time periods. Despite the value of new methods, stepped wedge trials still have statistical disadvantages compared to other trial designs in epidemic settings.

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