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Power analysis (power 0.8; α 0.05) indicated a sample size requirement of seven knees for valid comparisons.
Power analysis (power 0.8; α 0.05; detectable difference 8.0; standard deviation 5.1) indicated a sample size requirement of 15 subjects for valid comparisons.
Power calculations indicated a sample size of 12 for each group was needed resulting in the subset of 54 (Moormann, manuscript in preparation).
These parameters indicated a sample size of approximately 15 per group.
All of these, however, indicated a sample size larger than what could be expected from the inclusion rate.
A sample size calculation (5% significance level, 80% power, 33% effect and 20% dropout rate) indicated a sample size of 500 will be necessary to see an effect on the fall rate.
Similar(51)
Our power calculations indicate a sample size of 112 is required for both primary outcomes.
Experiences from our own earlier studies [ 16, 17] indicate a sample size of 10 to 15 persons per setting.
Again, the two QTL categories encompassing the smallest number of base pairs had the highest number of correlated GO terms, possibly indicating a sample size effect.
Based on the data in our systematic review, a sample size calculation using α = 0.05 and 1 – β = 0.80 indicates a sample size of 265 patients per arm, without dropout correction.
In other words a calculation indicating a sample size of 100 will generally rule out the need for a study of size 500 but not one of 110; a sample size of 187 can be usefully rounded up to 200, and so on.
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CEO of Professional Science Editing for Scientists @ prosciediting.com