Things to consider

Why conduct a power analysis?

  • To determine your sample size
  • To determine whether it is even possible to find an effect with the given means (technical settings, available budget for subjects)
  • To optimize your pre-processing software given your scanner settings

How to define an effect size?

  • Test statistic
  • Cluster extent
  • Relate one contrast of interest A to the strength of another contrast B → see Matan Mazor and David Mehler
  • Length of recording → number of trials

Tools for univariate power analysis

  • GPower, Pangea
  • Suited if clearly defined ROIs/ localizers are available
  • How to clearly define ROIs? How to define ROIs on a subject-specific level?
  • G*Power is suitable for very particular questions/ analyses, but require many decisions a-priori → defining ROIs, defining summary statistics on ROIs
  • Can even increase power (e.g. for very small volumes) because you avoid correction for multiple comparisons

Tools for 3-dimentional power analysis

  • Simulation: take available data set (resting-state) with a realistic noise profile, add an effect of a certain extent and strength, see if your (preprocessing + analysis) finds it
  • What are the parameters to vary?
    • Sample size
    • Effect strength/ extend
    • Noise profile
    • Using nuisance regressors or not