class_docstr: Results class for Engle-Granger cointegration tests.
  
  Parameters
  ----------
  stat : float
      The Engle-Granger test statistic.
  pvalue : float
      The pvalue of the Engle-Granger test statistic.
  crit_vals : Series
      The critical values of the Engle-Granger specific to the sample size
      and model dimension.
  null : str
      The null hypothesis.
  alternative : str
      The alternative hypothesis.
  trend : str
      The model's trend description.
  order : int
      The number of stochastic trends in the null distribution.
  adf : ADF
      The ADF instance used to perform the test and lag selection.
  xsection : RegressionResults
      The OLS results used in the cross-sectional regression.
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docstr: The maximum number of lags used in the lag-length selection.
docstr_tok: ["The","maximum","number","of","lags","used","in","the","lag-length","selection","."]
code: def max_lags(self) -> int | None:
      """The maximum number of lags used in the lag-length selection."""
      return self._adf.max_lags
  
imports: from __future__ import annotations
  import numpy
  import pandas
  from scipy import stats
  from statsmodels.iolib.summary import Summary
  from statsmodels.iolib.table import SimpleTable
  from statsmodels.regression.linear_model import RegressionResults
  from arch.typing import ArrayLike1D, ArrayLike2D, Literal, UnitRootTrend
  from arch.unitroot._shared import ResidualCointegrationTestResult, _check_cointegrating_regression, _cross_section
  from arch.unitroot.critical_values.engle_granger import CV_PARAMETERS, LARGE_PARAMETERS, SMALL_PARAMETERS, TAU_MAX, TAU_MIN, TAU_STAR
  from arch.unitroot.unitroot import ADF, TREND_DESCRIPTION
label_desc: Use image node_id 3 for calling the EngleGrangerTestResults obj's underlying member method code with example usage: obj.max_lags() and returns: self