def z_score(self, baseline=0.0):
"""Return a parametric estimation of the z-score associated
with the null hypothesis: (H0) 'contrast equals baseline'
Parameters
==========
baseline: float, optional,
Baseline value for the test statistic
"""
if self.p_value_ == None or not self.baseline == baseline:
self.p_value_ = self.p_value(baseline)
# Avoid inf values kindly supplied by scipy.
self.z_score_ = z_score(self.p_value_)
return self.z_score_
def z_score(self, baseline=0.0):
"""Return a parametric estimation of the z-score associated
with the null hypothesis: (H0) 'contrast equals baseline'
Parameters
==========
baseline: float, optional,
Baseline value for the test statistic
"""
if self.p_value_ == None or not self.baseline == baseline:
self.p_value_ = self.p_value(baseline)
# Avoid inf values kindly supplied by scipy.
self.z_score_ = z_score(self.p_value_)
return self.z_score_
def z_score(self, baseline=0.0):
"""Return a parametric estimation of the z-score associated
with the null hypothesis: (H0) 'contrast equals baseline'
Parameters
----------
baseline: float, optional
Baseline value for the test statistic
Notes
-----
The value of 0 is used where the stat is not defined
"""
if self.p_value_ is None or not self.baseline == baseline:
self.p_value_ = self.p_value(baseline)
# Avoid inf values kindly supplied by scipy.
self.z_score_ = z_score(self.p_value_)
self.z_score_[np.isnan(self.stat_)] = 0
return self.z_score_
def z_score(self, baseline=0.0):
"""Return a parametric estimation of the z-score associated
with the null hypothesis: (H0) 'contrast equals baseline'
Parameters
----------
baseline: float, optional
Baseline value for the test statistic
Notes
-----
The value of 0 is used where the stat is not defined
"""
if self.p_value_ is None or not self.baseline == baseline:
self.p_value_ = self.p_value(baseline)
# Avoid inf values kindly supplied by scipy.
self.z_score_ = z_score(self.p_value_)
self.z_score_[np.isnan(self.stat_)] = 0
return self.z_score_
