def METHOD_NAME(self, dataset, drop_invalid=True):
    """Fit Estimator to Dataset.
    Parameters
    ----------
    dataset : :obj:`~nimare.dataset.Dataset`
        Dataset object to analyze.
    drop_invalid : :obj:`bool`, optional
        Whether to automatically ignore any studies without the required data or not.
        Default is False.
    Returns
    -------
    :obj:`~nimare.results.MetaResult`
        Results of Estimator fitting.
    Attributes
    ----------
    inputs_ : :obj:`dict`
        Inputs used in _fit.
    Notes
    -----
    The `fit` method is a light wrapper that runs input validation and
    preprocessing before fitting the actual model. Estimators' individual
    "fitting" methods are implemented as `_fit`, although users should
    call `fit`.
    """
    self._collect_inputs(dataset, drop_invalid=drop_invalid)
    self._preprocess_input(dataset)
    maps, tables, description = self._fit(dataset)
    if hasattr(self, "masker") and self.masker is not None:
        masker = self.masker
    else:
        masker = dataset.masker
    return MetaResult(self, mask=masker, maps=maps, tables=tables, description=description)