(effects, nsubs)
return (W * effects).sum()
Combining effects for meta-analysis statistics

    Function that takes effects from each experiments and number of subjects to
    return meta-analysis effect

    Parameters
    ----------
    p: DataFrame
        effects for 2 pipelines computed on different datasets
    nsubs: float
        average number of subject per datasets

    Returns
    -------
    effect: float
        Estimatation of the combined p-value
Combining effects for meta-analysis statistics
Combining effects for meta - analysis statistics
def combine_effects(effects, nsubs):
    """Combining effects for meta-analysis statistics

    Function that takes effects from each experiments and number of subjects to
    return meta-analysis effect

    Parameters
    ----------
    p: DataFrame
        effects for 2 pipelines computed on different datasets
    nsubs: float
        average number of subject per datasets

    Returns
    -------
    effect: float
        Estimatation of the combined p-value
    """
    W = np.sqrt(nsubs)
    W = W / W.sum()
    return (W * effects).sum()
def combine_effects ( effects , nsubs ) : W = np . sqrt ( nsubs ) W = W / W . sum ( ) return ( W * effects ) . sum ( )