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indrajeetpatil.github.io
| | www.cedricscherer.com
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| | A step-by-step tutorial explaining how my visualizations have evolved from a typical basic ggplot. Here, I transform a basic boxplot into a compelling and self-explanatory combination of a jittered dot strip plot and a lollipop plot.
| | echarts4r.john-coene.com
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| | patchwork.data-imaginist.com
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| | www.rdatagen.net
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| A key challenge - maybe the key challenge - of a stepped wedge clinical trial design is the threat of confounding by time. This is a cross-over design where the unit of randomization is a group or cluster, where each cluster begins in the control state and transitions to the intervention. It is the transition point that is randomized. Since outcomes could be changing over time regardless of the intervention, it is important to model the time trends when conducting the efficacy analysis. The question is how we choose to model time, and I am going to suggest that we might want to use a very flexible model, such as a cubic spline or a generalized additive model (GAM).