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Despite a good participation rate, the relatively small population of STEM GTAs who primarily teach (rather than grade), even at a medium-sized research institution, made generating a sample size of sufficient power difficult.
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This generated a sample size of 31 participants per group.
We used a bootstrap procedure (and the bias corrected method) that generated a sample size of 5000 for our regression analyses (Shrout & Bolger 2002).
This generates a sample size of 43 subjects per group.
This generated a sample size of at least 16 participants per group.
However, the aim of this pilot study was to provide novel data to support the underlying rationale and generate a sample size for a subsequent experimental trial.
The number of prescriptions audited was empirically determined in order to generate a sample size equivalent to a large study recently undertaken in the UK.
As that study did not use oocytes with known staging, we examined metaphase arrested nod oocytes from females with exchange X chromosomes (which have very high rates of 4 loss and a much lower rate of X loss, limited to those 6 10% of meioses with spontaneously nonexchange X chromosomes), and generated a sample size that allows estimation of segregation class frequencies.
For each combination of the test functions, noise types, and SNR, 100 datasets were generated with a sample size of 1024.
For each of the 60 situations, 1000 different data sets were generated with a sample size of 2000 subjects.
Tree topologies and posterior probability node support values were generated from a sample size of 100 trees following a 20% burn-in.
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CEO of Professional Science Editing for Scientists @ prosciediting.com