Points of significance: Power and sample size
By Martin Krzywinski, Naomi Altman. Nature Methods, 2013
193 citations recorded by the source corpus.
Subfields: Molecular Biology, Small Animals, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/50de7b259b902f21a73bda0775b6768650481bde
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In Molecular Biology
In Small Animals
In Statistics and Probability
Citations in the corpus
- Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies (2020, methodology): “In addition, post-hoc power analysis (possible with G-Power, PASS) following the study significantly facilitates the evaluation of the results in clinical studies.”
- Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: a tutorial (2018, unknown): “…attention should be paid to proper randomization and blocking (Krzywinski & Altman, 2014a) of a sufficient number of biological and technical sample replicates (Blainey et al , 2014) to ensure optimal statistical power (Krzywinski & Altman, 2013) during the downstream data analysis process.”