Why Sample Size Calculators Give Different Answers and Which Result to Trust
Different sample-size answers usually reflect different assumptions. Learn how to find the setting that changed the result.
Read guide →Sample Size and Study Design Guides
Use these guides before data collection to document the assumptions behind recruitment targets. The collection explains why calculators disagree, how repeated measurements affect power, and how to separate an analyzable target from the number that must be recruited.
Core answer
A defensible sample size follows from the primary hypothesis, statistical model, effect-size definition, alpha, power, allocation, design effects, and expected loss to follow-up.
Repeated-Measures ANOVA Sample Size: Inputs, Examples, and Pitfalls
Repeated-measures sample size depends on more than the number of groups. Correlation, sphericity, interaction targets, and dropout can materially change the result.
Read guide →How to use this collection
Begin with the guide closest to your immediate decision. Record the assumptions, settings, and definitions you use, then open the linked DataStatPro workflow to apply the method. Educational examples should be adapted to the actual study protocol and data structure.