code: def one_sample_ftest(Y, V1, n_iter=5, verbose=False):
      """Returns the mixed effects F-stat for each row of the X
      (one sample test)
      This uses the Formula in Roche et al., NeuroImage 2007
  
      Parameters
      ----------
      Y: array of shape (n_samples, n_tests)
         the data
      V1: array of shape (n_samples, n_tests)
          first-level variance ssociated with the data
      n_iter: int, optional,
             number of iterations of the EM algorithm
      verbose: bool, optional, verbosity mode
  
      Returns
      -------
      fstat, array of shape (n_tests),
             statistical values obtained from the likelihood ratio test
      sign, array of shape (n_tests),
            sign of the mean for each test (allow for post-hoc signed tests)
      """
      return mfx_stat(
          Y,
          V1,
          np.ones((Y.shape[0], 1)),
          0,
          n_iter=n_iter,
          verbose=verbose,
          return_t=False,
          return_f=True,
      )[0]
  
file_path: nipy/nipy/algorithms/statistics/mixed_effects_stat.py
imports: import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: one_sample_ftest(Y, V1, n_iter, verbose) and returns: mfx_stat