Power and Sample Size

Use this overview to decide when power and sample size planning is the right starting point, choose between sample size estimation and minimal effect planning, and understand what belongs in a different methods category.

Use this section when your question is how many observations you need, what effect size you can reasonably detect, or what minimum effect would be scientifically meaningful before you run the main analysis.

This section is for study planning and design decisions, not for running the main statistical analysis or interpreting completed results. If your main question is about comparing groups or fitting a model to observed data, start with Group Comparison or Regression and Modeling instead.

Power and sample size methods are useful when you need to set assumptions about alpha, power, variance, baseline rates, or target effect size before data collection or before finalizing an analysis plan. Licklider helps you choose whether you are estimating sample size from a design target or defining the smallest effect that should count as meaningful.

Child pages

Start here

  1. Start with Power Analysis and Sample Size Calculation when you need to estimate required sample size, achievable power, or detectable effect size for a planned design.
  2. Start with Minimal Effect of Interest when you need to define the smallest effect that would change a scientific or practical decision before choosing sample size targets.
  • Use related links below when your planning question also needs setup, checks, reporting, or downstream methods guidance.