This is a clinical decision, not a statistical one, and the values need to be established before the sample size calculation is done.
As the trial was stopped before the sample size was reached, we post hoc decided to conduct sequential analysis to assess the results of significance testing taking sparse data and repetitive testing into consideration.
The main reason this method could not maintain empirical power at 80% under a negative misspecification is that too many trials stopped for futility before the sample size could be re-estimated and all of the type II error was used up at the interim analysis.
Psychological data were collected for 27 women recalled for second scans in year 1 and for 11 women who were recalled in year 2. The data did not indicate a significant increase in anxiety before the second scan, although the sample sizes are too small to make any general conclusions about the impact of false-positive MRI scans.
■ To account for unexpected euthanasia of mice before the end of the experiment or exclusion of mice before treatment, the sample size was increased by ∼ 30%.
We noted that omega-3 fatty acid supplementation reduced the risk of total mortality only when we included trials published before 2000, the sample size was less than 1000, the proportion of men in the population was more than 80%, or participants received alpha-linolenic acid.
Many of these existing experiment design software work for ideal situation (i.e., before sample collection) where the sample size is fixed and/or model is specified.
Before starting the trial, the sample size of the study (310 patients) was calculated so that the non-inferiority of iobitridol (350 mgI/ml) in providing the same level of diagnostic information as iomeprol (400 mgI/ml) could be statistically demonstrated with 80% power and 5% type-one error.
Unconventional monetary tools were only rarely used before the crisis, which means the sample size of case studies is small.
More formally, if the sample size before adaptation is n, the samples are {x 1,x 2,…,x n }, and m of them are to be removed, the first sample to be removed (x_{r_{1}}) is selected by drawing r 1 from the set {1,2,…,n} with the uniform probability of 1/n.
