class_docstr: Analyses for a collection of 2x2 contingency tables.
  
  Such a collection may arise by stratifying a single 2x2 table with
  respect to another factor.  This class implements the
  'Cochran-Mantel-Haenszel' and 'Breslow-Day' procedures for
  analyzing collections of 2x2 contingency tables.
  
  Parameters
  ----------
  tables : list or ndarray
      Either a list containing several 2x2 contingency tables, or
      a 2x2xk ndarray in which each slice along the third axis is a
      2x2 contingency table.
  
  Notes
  -----
  This results are based on a sampling model in which the units are
  independent both within and between strata.
class_docstr_tok: ["Analyses","for","a","collection","of","2x2","contingency","tables",".","Such","a","collection","may","arise","by","stratifying","a","single","2x2","table","with","respect","to","another","factor",".","This","class","implements","the","'Cochran-Mantel-Haenszel","'","and","'Breslow-Day","'","procedures","for","analyzing","collections","of","2x2","contingency","tables",".","Parameters","--","--","--","--","--","tables",":","list","or","ndarray","Either","a","list","containing","several","2x2","contingency","tables",",","or","a","2x2xk","ndarray","in","which","each","slice","along","the","third","axis","is","a","2x2","contingency","table",".","Notes","--","--","-","This","results","are","based","on","a","sampling","model","in","which","the","units","are","independent","both","within","and","between","strata","."]
docstr: Returns the logarithm of the pooled odds ratio.
  
  See oddsratio_pooled for more information.
docstr_tok: ["Returns","the","logarithm","of","the","pooled","odds","ratio",".","See","oddsratio_pooled","for","more","information","."]
code: def logodds_pooled(self):
      """
      Returns the logarithm of the pooled odds ratio.
  
      See oddsratio_pooled for more information.
      """
      return np.log(self.oddsratio_pooled)
  
imports: import warnings
  import numpy
  import pandas
  from scipy import stats
  from statsmodels import iolib
  from statsmodels.tools import sm_exceptions
  from statsmodels.tools.decorators import cache_readonly
label_desc: Use image node_id 5 for calling the StratifiedTable obj's underlying member method code with example usage: obj.logodds_pooled() and returns: np