Sample size and power
Sample size planning links the primary research question to the variability, expected effect, acceptable error and analysis strategy. Bigger samples cannot eliminate systematic bias.
Open interactive lesson & self-check ↗Sample size and power — learning map
Original conceptual SVG · scalableOriginal schematic relationship map for this topic; relationships are organized for study, not intended as an anatomical depiction or a diagnostic algorithm.
Primary endpoint
Specify the outcome type, measurement scale, clinically meaningful effect and comparison strategy before selecting a sample-size formula.
Variability and event frequency
Estimates of dispersion or baseline event frequency affect precision and power; justify them with pilot information or relevant prior studies.
Error and power
A conventional power calculation states type-I error, desired power and assumptions under a defined alternative, not a guarantee of a significant result.
Feasibility and ethics
Allow for attrition, clustering or repeated measures where relevant, and document assumptions before recruitment.
Reference and next reading
Explore the original curriculum and publisher-hosted resources for full-depth reading; this note is an original schematic introduction, not an exhaustive chapter.