{"id":23082652,"url":"https://github.com/kkmann/unblinded-sample-size-adaptation","last_synced_at":"2026-02-15T21:33:43.104Z","repository":{"id":47754890,"uuid":"274669694","full_name":"kkmann/unblinded-sample-size-adaptation","owner":"kkmann","description":"Sample Size Recalculation, When and How? 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Sample Size Recalculation, When and How?\n\nThe preprint is available at https://arxiv.org/abs/2010.06567\n\nAdapting the final sample size of a trial to the evidence accruing\nduring the trial is a natural way to address planning uncertainty.\nSince the sample size is usually determined by an\nargument based on the power of the trial,\nan interim analysis raises the question of\nhow the final sample size should be determined conditional on the accrued information.\nTo this end, we first review and compare common approaches to estimating conditional power\nwhich is often used in heuristic sample size recalculation rules.\nWe then discuss the connection of heuristic sample size recalculation and\noptimal two-stage designs demonstrating that the latter is the superior approach in a fully pre-planned setting.\nHence, unplanned design adaptations should only be conducted\nas reaction to trial-external new evidence, operational needs to violate the originally chosen design,\nor \\textit{post~hoc} changes in the optimality criterion but not as a reaction to trial-internal data.\nWe are able to show that commonly discussed sample size recalculation rules lead to paradoxical adaptations\nwhere an initially planned optimal design is not invariant under the adaptation rule\neven if the planning assumptions do not change.\nFinally, we propose two alternative ways of reacting to\nnewly emerging trial-external evidence in ways that are consistent with the originally\nplanned design to avoid such inconsistencies.\n\nFeel free to explore the repository interactively using the binder badge powered by https://mybinder.org or clone and explore locally.\n\n`R` script files for reproducing the results are available in the `R` folder.\nThe required dependencies can be installed using the\n[`renv`](https://rstudio.github.io/renv/articles/renv.html) \npackage and the provided lockfile `renv.lock`.\nA bash script `run` to execute all code is provided. \nOn Linux/Unix, execute \n```\n./run\n```\n(might take a while).\nPlots are stored in `output/figures`.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkkmann%2Funblinded-sample-size-adaptation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkkmann%2Funblinded-sample-size-adaptation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkkmann%2Funblinded-sample-size-adaptation/lists"}