To maximize power and minimize sample size effects, an alpha value larger or equal to 0.05 was sought.
From samples with >100 individuals available (Table 1), a sub-set of 100 individuals was chosen at random for subsequent analyses in order to minimize sample size effects.
Innovative clinical trial methods minimize sample size requirements (n=4) and maximize the proportion of patients who receive active treatment (n=2), strategies crucial to studying small populations of patients with limited treatment choices.
Thus, further cleaning (baking) of reagents and glasswares should minimize sample size of the HT Zn reduction method to 0.025 mg of C. In conclusion, the HT Zn reduction method had a mean background mc of 0.011 mg of C and a mean background Fc of 1.5445.
This choice was supported by observing that for K=10, (1) the global likelihood maximum was indeed probably reached and (2) the CV index values were close to the lowest ones at K=9. Subsequently, a sub-set of 24 individuals was chosen at random from each European and Near-Eastern ancestry population for the following analyses in order to minimize sample size effects.
This quality minimizes sample-size problems and makes points highly suitable for quantitative analyses not always valid or practical in other artifact classes (e.g., ceramics, the vast majority of which occur as fragmented sherds, not integral vessels).
The observed clustering of outcomes minimizes the sample size required for statistical modeling.
Both biomarkers and clinical outcomes have been considered for each of these two applications, and generally, decisions will be made in a way that minimizes the sample size requirement for a clinical study, but it is helpful to evaluate the assumptions behind this criterion for evaluation.
In order to minimize small sample size related biases, we removed gene sets that contained either <5 HGT events, <5 distinct genera, or <10 distinct genomes.
Design parameters are chosen to minimize expected sample size subject to frequentist error constraints.
The goal of the method is to minimize the sample size while keeping the AKV values of all tested soil variables below given thresholds.
