Equivalent Sample Size. For example for a difference of 09 the analyst needs a sample size of at least 289 observations in each group to achieve a power of 09. When the difference is closer to the upper equivalence limit 05 the power of the test is lower.
The log-likelihood Lthetabf X log left pbf Xtheta right scales with the sample size since it is a function of the data while the prior density does not. F α β Φ -1 α Φ -1 β 2. This calculator uses the following formulas to compute sample size and power respectively.
Φ -1 is the cumulative distribution function of a standardised normal deviate.
When the difference is closer to the lower equivalence limit 1 or the upper equivalence limit 1 then the analyst needs a larger sample size to achieve the same power. 100 π d 2. For example if a survey of 1000 people has an effective sample size for a statistic of 500 it means that the amount of sampling error is equivalent to that which would have been obtained by a study of 500 people that did not need to be weighted. A sample of size n16448 will ensure that a 95 confidence interval estimate of the prevalence of breast cancer is within 010 or to within 10 women per 10000 of its true value.
