The phrase "approaches sample size" is correct and usable in written English.
It can be used in contexts related to research, statistics, or experimental design when discussing the adequacy of a sample size in relation to a target or desired size.
Example: "As the study progresses, we are pleased to report that our participant count approaches sample size, allowing for more reliable results."
Alternatives: "nears the required sample size" or "is close to the target sample size".
From a statistical point of view, as reviewed by Simon [14], this type of prediction is a complicated problem and many factors, such as gene selection rules, sample resubstitution approaches, sample size concerns, and classification methods are involved.
Through such an approach, sample size could be greatly increased to yield a more complete characterization of the student community in a particular school system.
In this approach, sample size for clustered randomized trials was estimated taking into account the role of the planned trial on a future meta-analysis [ 48].
Based on previous investigation [ 7], a large effect size was anticipated, but to use a conservative approach, sample size was calculated using a medium effect size corresponding to a 25% relative increase in postexercise apoptosis.
In this approach sample size requirements are dependent on both the frequency of injury events and the correlation of psychological states over time (higher sample sizes if states are relatively stable because there is less information on the changing exposures).
Quite a few studies have also analyzed the effect of aberrant DNA methylation on MS phenotypes, using various approaches in sample size, definitions, methodology, and statistical approach, and they have come upon various results.
It is clear that the calculated genetic diversity for a given genomic region will depend upon the sampling approach and sample size.
Approaches to sample size and power calculations have been provided, but a simple sample size formula is lacking.
We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples.
A simulation-based algorithm allows consideration of variable cluster sizes and intracluster correlation coefficient values in conjunction with three approaches to sample size estimation, namely the power-based, variance reduction and non-inferiority perspectives.
These papers did not report approaches to sample size and statistical power estimation.
