PASSED: Calculate Power and Sample Size for Two Sample Tests

Abstract:

Power and sample size estimation are critical aspects of study design to demonstrate minimized risk for subjects and justify the allocation of time, money, and other resources. Researchers often work with response variables that take the form of various distributions. Here, we present an R package, PASSED, that allows flexibility with seven common distributions and multiple options to accommodate sample size or power analysis. The relevant statistical theory, calculations, and examples for each distribution using PASSED are discussed in this paper.

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Published

Oct. 18, 2021

Received

Feb 8, 2021

DOI

10.32614/RJ-2021-094

Volume

Pages

13/2

542 - 560

CRAN packages used

PASSED, samplesize, TrialSize, simglm, stats, pwr, MESS, pwr2ppl, WebPower, MKmisc

CRAN Task Views implied by cited packages

ClinicalTrials

Footnotes

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    Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

    Citation

    For attribution, please cite this work as

    Li, et al., "The R Journal: PASSED: Calculate Power and Sample Size for Two Sample Tests", The R Journal, 2021

    BibTeX citation

    @article{RJ-2021-094,
      author = {Li, Jinpu and Knigge, Ryan P. and Chen, Kaiyi and Leary, Emily V.},
      title = {The R Journal: PASSED: Calculate Power and Sample Size for Two Sample Tests},
      journal = {The R Journal},
      year = {2021},
      note = {https://doi.org/10.32614/RJ-2021-094},
      doi = {10.32614/RJ-2021-094},
      volume = {13},
      issue = {2},
      issn = {2073-4859},
      pages = {542-560}
    }