The FactorialPowerPlan macro can be used to do sample size and power calculations for planning either a factorial or fractional factorial experiment. The calculations can be done for either posttest-only or pretest-posttest designs. Participants can either be assumed to be independent, or nested within existing clusters as discussed in Dziak, Nahum-Shani, and Collins (2012).

The macro can be used for three separate purposes:

  • to calculate statistical power based on an available sample size and assumed effect size,
  • to calculate required sample size based on a desired statistical power and an assumed effect size, or
  • to calculate minimum detectable effect size based on available sample size and desired statistical power.


Recommended Citations

FactorialPowerPlan (Version 1.0) [Software]. (2013). University Park: The Methodology Center, Penn State.

Dziak, J. J., Collins, L. M. & Wagner, A. T. (2013). FactorialPowerPlan users’ guide (Version 1.0). University Park: The Methodology Center, Penn State.


The FactorialPowerPlan() function in the R ‘MOST’ package estimates the power, detectable effect size, or required sample size of a factorial or fractional factorial experiment, for main effects or interactions, given several possible choices of effect size metric, and allowing pretests and clustering.

There are three ways to use this function:

  • estimate power available from a given sample size and a given effect size,
  • estimate sample size needed for a given power and a given effect size, or
  • estimate effect size detectable from a given power at a given sample size.


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