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Power and sample size

Before you conduct your experiment, determine the sample size needed to detect meaningful effects without wasting resources. Do you intend to perform tests of means, variances, proportions, or correlations? Do you plan to fit a one-way, two-way, or repeated-measures ANOVA model? Do you want to fit a Cox proportional-hazards model or compare survivor functions using a log-rank test? Use Stata's power commands or interactive Control Panel to compute power and sample size, create customized tables, and automatically graph the relationships between power, sample size, and effect size for your planned study. And much more.

Learn about power and sample-size analysis.
Watch A tour of power and sample size.
Watch additional Power and sample-size features.

Classic comparisons

ANOVA

  • One-way models
  • Two-way models
  • Repeated-measures models

Linear regression

  • Slope test
  • Coefficient-of-determination test
  • Partial-correlation test

Contingency tables

  • Cochran—Mantel—Haenszel test
  • Matched case—control studies
  • Cochran—Armitage trend test

Cluster randomized designs

  • One-sample mean
  • Two-sample means
  • One-sample proportion
  • Two-sample proportions
  • Log-rank test

Survival analysis

  • Log-rank test of survival functions
  • Cox proportional hazards model
  • Exponential regression
  • Clustered data

Solve for

  • Power
  • Sample size
  • Number of clusters
  • Cluster size
  • Effect size (minimum detectable effect)

Specify lists of

  • Alpha values
  • Power levels
  • Beta values
  • Sample sizes
  • Ratios of sample sizes
  • And more

Multiple scenarios using

  • All combinations of values
  • Parallel lists of values

Control panel interface

  • Select analysis type from descriptive summaries
  • Specify list of power, sample size, or other levels
  • Automated tables and graphs
  • Customize tables and graphs
  • Command interface too (of course)

Designs

Tables

  • Automated
  • Customized

Graphs

  • Automated
  • Customized
  • Simple or comparative

Save results to dataset

Add your own methods

Additional resources

Watch Power and sample size tutorials

Also see precision and sample-size analysis for confidence intervals.


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