gemmr.sample_size.linear_model.cca_req_corr¶
-
gemmr.sample_size.linear_model.
cca_req_corr
(X, Y, n_req, criterion='combined', algorithm='linear_model', target_power=0.9, target_error=0.1, data_home=None)¶ Determines the minimum required true correlation to achieve power and error levels.
Parameters: - X (np.ndarray (n_samples, n_X_features) or int >= 2) – either a data matrix or directly the number of features for data matrix \(X\)
- Y (np.ndarray (n_samples, n_Y_features) or int >= 2) – either a data matrix or directly the number of features for data matrix \(Y\)
- n_req (sample_size) – available sample size
- criterion (str) –
criterion according to which sample sizes are estimated. Can be:
'combined'
'power'
'association_strength'
'weight'
'score'
'loading'
'crossloading'
- algorithm (str) –
algorithm used to calculate sample sizes. Can be:
'linear_model'
- target_power (float between o and 1) – if
criterion
is'combined'
or'power'
sample size is chosen to obtain at leasttarget_power
power - target_error (float between 0 and 1) – if criterion is not
'power'
sample size is chosen to obtain at mosttarget_error
error in error metric(s) - data_home (None or str) – path where outcome data are stored,
None
indicates default path
Returns: req_corr – minimum required true correlation
Return type: float