models.py 文件源码

def _cond_ind_effects_wrapper(self):
        """
        A wrapper for the conditional indirect effects.
        :return: pd.DataFrame
            A DataFrame of effects, se, llci, and ulci, for the conditional indirect effects.
        """
        symb_to_var = self._symb_to_var
        results = self.estimation_results
        rows_stats = np.array([results["effect"], results["se"], results["llci"], results["ulci"]]).T
        cols_stats = ["Effect", "Boot SE", "BootLLCI", "BootULCI"]

        mod_values = self._moderators_values
        med_values = [[symb_to_var.get('m{}'.format(i + 1), 'm{}'.format(i + 1)) for i in range(self._n_meds)]]
        values = med_values + mod_values

        rows_levels = np.array([i for i in product(*values)])
        cols_levels = ["Mediator"] + [symb_to_var.get(x, x) for x in self._moderators_symb]

        rows = np.concatenate([rows_levels, rows_stats], axis=1)
        cols = cols_levels + cols_stats
        df = pd.DataFrame(rows, columns=cols, index=[""] * rows.shape[0])
        return df.apply(pd.to_numeric, args=["ignore"])