def _augment_exog(self, group_ix):
        ex_r = self.exog_re_li[group_ix] if self.k_re > 0 else None
        if self.k_vc == 0:
            return ex_r

        group = self.group_labels[group_ix]
        ex = [ex_r] if self.k_re > 0 else []
        any_sparse = False
        for j,k in enumerate(self._vc_names):
            if group not in self.exog_vc[k]:
                continue
            ex.append(self.exog_vc[k][group])
            any_sparse |= sparse.issparse(ex[-1])
        if any_sparse:
            for j, x in enumerate(ex):
                if not sparse.issparse(x):
                    ex[j] = sparse.csr_matrix(x)
            ex = sparse.hstack(ex)
            ex = sparse.csr_matrix(ex)
        else:
            ex = np.concatenate(ex, axis=1)

        return ex
Concatenate the columns for variance components to the columns
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/regression/mixed_linear_model.py/MixedLM._augment_exog