class_docstr: Class to contain results from likelihood models 
class_docstr_tok: ["Class","to","contain","results","from","likelihood","models"]
docstr: Return the (Wald) t-statistic for a given parameter estimate.
  
  Use Tcontrast for more complicated (Wald) t-statistics.
docstr_tok: ["Return","the","(","Wald",")","t-statistic","for","a","given","parameter","estimate",".","Use","Tcontrast","for","more","complicated","(","Wald",")","t-statistics","."]
code: def t(self, column=None):
      """
      Return the (Wald) t-statistic for a given parameter estimate.
  
      Use Tcontrast for more complicated (Wald) t-statistics.
      """
  
      if column is None:
          column = list(range(self.theta.shape[0]))
  
      column = np.asarray(column)
      _theta = self.theta[column]
      _cov = self.vcov(column=column)
      if _cov.ndim == 2:
          _cov = np.diag(_cov)
      _t = _theta * pos_recipr(np.sqrt(_cov))
      return _t
  
imports: import numpy
  from nibabel.onetime import auto_attr
  from numpy.linalg import inv
  from scipy.stats import t
  from ...utils.matrices import pos_recipr
label_desc: Use image node_id 5 for calling the LikelihoodModelResults obj's underlying member method code with example usage: obj.t(column) and returns: _t