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fharrell.com | ||
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www.kenkoonwong.com
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| | | | | In my simulations of Response Adaptive Randomization, I discovered it performs comparably to fixed 50-50 allocation in identifying treatment effects. The adaptive approach does appear to work! However, with only 10 trials, I've merely scratched the surface. Important limitations exist - temporal bias risks, statistical inefficiency, and complex multiplicity adjustments in Bayesian frameworks. | |
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hbiostat.org
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| | | | | This article provides a demonstration that the perceived non-robustness of nonlinear models for covariate adjustment in randomized trials may be less of an issue than the non-transportability of marginal so-called robust estimators. | |
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www.rdatagen.net
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| | | | | Simulation can be super helpful for estimating power or sample size requirements when the study design is complex. This approach has some advantages over an analytic one (i.e.one based on a formula), particularly the flexibility it affords in setting up the specific assumptions in the planned study, such as time trends, patterns of missingness, or effects of different levels of clustering. A downside is certainly the complexity of writing the code as well as the computation time, which can be a bit painful. My goal here is to show that at least writing the code need not be overwhelming. | |
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brunomioto.com
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| | | Getting started with data visualization | ||
