Principles of Sample Size Calculation
2. Why Sample Size is Important?
2.1. Components of Sample Size Calculations
Component |
Definition |
Alpha (α) (Type I error) |
The probability of falsely rejecting the null hypothesis (H_{0}) and detecting a statistically significant difference when the groups in reality are not different, i.e. the chance of a false-positive result. |
Beta (β) (Type II error) |
The probability of falsely accepting H_{0} and not detecting a statistically significant difference when a specified difference between the groups exists in reality, i.e. the chance of a false-negative result. |
Power (1-β) |
The probability of correctly rejecting H_{0} and detecting a statistically significant difference when a specified difference between the groups in reality exists. |
Minimal clinically relevant difference |
The minimal difference between the groups that the investigator considers biologically plausible and clinically relevant. |
Variance |
The variability of the outcome measure, expressed as the Standard Deviation (SD) in case of a continuous outcome. |
Abbreviations: H_{0} – null hypothesis; the null hypothesis states that compared groups are not different from each other). SD – standard deviation.