code: def f_threshold_mway_rm(
      n_subjects, factor_levels, effects="A*B", pvalue=0.05
  ):
      """Compute F-value thresholds for a two-way ANOVA.
  
      Parameters
      ----------
      n_subjects : int
          The number of subjects to be analyzed.
      factor_levels : list-like
          The number of levels per factor.
      effects : str
          A string denoting the effect to be returned. The following
          mapping is currently supported:
  
              * ``'A'``: main effect of A
              * ``'B'``: main effect of B
              * ``'A:B'``: interaction effect
              * ``'A+B'``: both main effects
              * ``'A*B'``: all three effects
  
      pvalue : float
          The p-value to be thresholded.
  
      Returns
      -------
      F_threshold : list | float
          List of F-values for each effect if the number of effects
          requested > 2, else float.
  
      See Also
      --------
      f_oneway
      f_mway_rm
  
      Notes
      -----
      .. versionadded:: 0.10
      """
      effect_picks, _ = _map_effects(len(factor_levels), effects)
  
      F_threshold = []
      for _, df1, df2 in _iter_contrasts(
          n_subjects, factor_levels, effect_picks
      ):
          F_threshold.append(stats.f(df1, df2).isf(pvalue))
  
      return F_threshold if len(F_threshold) > 1 else F_threshold[0]
  
file_path: mne-python/mne/stats/parametric.py
imports: from functools import reduce
  from string import ascii_uppercase
  import numpy
  from scipy import stats
  from scipy.signal import detrend
  from ..utils import _check_option
label_desc: Use image node_id 7 for calling a global function with example usage: f_threshold_mway_rm(n_subjects, factor_levels, effects, pvalue) and returns: unknown