The fixed sample sizes correspond to fixed sample designs with pairwise alpha A2 and power Ω2.
For fixed sample size n, the detection power of the control chart can be computed.
In a classical fixed sample design, the sample size is set in advance of collecting any data.
In particular, we intend to provide more general results for sample size determination when a large number of parameter values need to be computed for a fixed sample.
To illustrate the potential contribution of adaptive trials we discuss fixed sample size design including event and time to event studies.
Furthermore, the performance of the proposed VSSI control charts and the fixed sample sizes and sampling intervals control charts are compared by numerical analysis results.
We validate the methodology with a simulation study that includes a comparison to Neyman Pearson and Bayesian fixed sample size test designs and the Wald SPRT.
Typically, for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows.
For fixed sample imaging, Zeiss LSM510 or Pascal confocal microscopes and LSM software were used.
Statistical power is increased whenever the tested effect size (predictivity in our context) is larger and the variance is smaller (assuming fixed sample size for simplicity).
Utilizing extreme phenotypes increases the odds ratio of association, with improved power to identify novel association signals under fixed genotyping budgets and fixed sample sizes.
