Description Usage Arguments Details Value Author(s) See Also Examples
It determines the ratio between the sample size of power analysis and precision analysis analysis and also, give the required sample sizes.
1 |
pR |
Incidence rate for the reference group |
pT |
Incidence rate for the test group |
sigr |
Variability in the reference group |
sigt |
Variability in the test group |
c |
Constant value for allowance of maximum error margin |
alpha |
Level of significance |
beta |
The probability of type-II error |
A pre-study power analysis for sample size determination is usually performed to calculate an appropriate sample size for achieving a desired power for detecting a clinically meaningful difference at a prespecified level of significance. In practice, a much larger sample size is expected for detecting a relatively smaller difference, especially for clinical trials with extremely low incidence rate. As a result, sample size determination based on power analysis may not be feasible. So, it is a good suggestion to determine the sample size based on precision analysis.
precsize returns 3 values:
Ratio between the sample size of power analysis and precision analysis
Sample size required for power analysis
Sample size required for precision analysis
Atanu Bhattacharjee, Rajashree Dey ,Soutik Halder and Akash Pawar
ABdesign crt.match crt.unmatch phsize prsize crsize
1 2 3 4 5 6 7 | # The incidence rate of reference group is pR = 0.8 per thousands and that of test group
# is pT = 0.7 per thousands. It is also assumed that the respective stanadard deviation
# of reference and test group are sigr = 2 and sigt = 1 respectively. The constant value
# is chosen c = 0.08 to allow the maximum marginal error. The level of significance is
# alpha = 0.05 and the probability of type-II error is beta = 0.20.
precsize(pR = 0.8, pT = 0.7, sigr = 2, sigt = 1, c = 0.08, alpha = 0.05, beta = 0.20)
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