kkmann/covid-19-screening-policies

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Created over 3 years ago
Updated over 1 year ago

kkmann/covid-19-screening-policies

kkmann

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Agent-based simulation results for school reopening policies during the Covid-19 pandemic.

adoptr

Adaptive optimal two-stage designs for clinical trials made easy.

workshop-r-swe

Website and materials of the workshop on GSWEP4R

describr

describr - publication quality descriptive tables with R

sample-size-calculation-under-uncertainty

Jupyter notebooks and companion shiny app for the manuscript 'A review of Bayesian perspectives on sample size derivation for confirmatory trials'.

Jupyter Notebook

adoptr-validation-report

R markdown-based validation report for the package adoptr.

unblinded-sample-size-adaptation

Sample Size Recalculation, When and How? https://arxiv.org/abs/2010.06567

quick-and-not-dirty-report

A template repository for quickly hosting a HTML version of a single .Rmd file on GitHub pages and make the repository interacitvely explorable using mybinder.org

pwcuratr

Curate gene pathway clusters using functional interactions

BinaryTwoStageDesigns

rmes

MVP for R package reliability knowledge-sharing protocol/platform

reproducibleresearch

material for reproducible research workshop @IEEE DSAA 2018

cov19sim

agent-based simulation of covid-19 for small populations

mrc-bsu-presentation-template

xarigan-based HTML/PDF slides template

optimal-binary-two-stage-designs

Jupyter Notebook

farringtonManning