presize: Precision-based sample size calculation for meaningful and conclusive clinical research results
Calculating the number of study participants is an essential part of clinical research. If the number of study participants is too small, study objectives cannot be fulfilled. On the other hand, an overly large number of study participants can result in a waste of resources. But how many participants does it take for a trial to draw meaningful and conclusive results?
There are two methods to calculate this number, which is also called the sample size:
- sample size calculation based on hypothesis testing (traditionally used)
- precision-based sample size calculation.
The precision-based sample size calculation method is more in line with the current trends towards presenting study results in the form of confidence intervals and away from p-values (Bland 2009). However, even if most statistical software packages contain some sample size calculation algorithms, they are mostly based on hypothesis testing.
To close this gap, statisticians at the CTU Bern have developed the presize R package, which provides a range of functions for performing precision-based sample size calculations. It includes methods for descriptive statistics, absolute and relative differences, various measures of correlation, and diagnostic measures.
The tool was developed on behalf of the SCTO’s Statistics & Methodology Platform and is one result of the platform’s grant for 2018. Read more about the two award winners below under “Grants to foster open-access statistical tools”.
R is a statistical computing programme and language commonly used in research. presize is now available on R’s main package repository CRAN. There is also a user-friendly web app that supports almost the entire functionality of presize for those who do not know R.