Data & Quality
Sample Size Calculation
Sample size calculation is the statistical process of determining the number of participants required for a clinical trial to detect a specified treatment effect with a defined Type 1 error rate, statistical power, and assumptions about variability.
Standard inputs include the minimum clinically important difference, the expected variability of the endpoint, the desired power (typically 80; 90%), the significance level (typically 0.05 two-sided), the expected dropout rate, and the analysis method.
Underpowered trials waste resources and patients; overpowered trials inflate cost and may slow enrollment. Adaptive designs use sample-size re-estimation to adjust mid-trial based on blinded interim variance estimates.
Related terms
Statistical Analysis Plan (SAP)
A Statistical Analysis Plan (SAP) is a detailed technical document that specifies, before database lock, every statistical analysis to be performed on a clinical trial's data, including primary and secondary endpoint analyses, handling of missing data, multiplicity adjustments, and sensitivity analyses.
Primary Endpoint
A primary endpoint is the pre-specified outcome measure on which a clinical trial's conclusions about efficacy or safety are principally based, used to power the sample size calculation and to test the trial's main hypothesis.
Adaptive Trial Design
An adaptive trial design is a clinical trial that uses pre-specified rules to modify aspects of the study (sample size, randomization ratio, dose, treatment arms, endpoints) based on accumulating interim data, without compromising scientific validity.
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