def METHOD_NAME(self, resid, values={}, override=False):
    """ Structure of values dict (dict entry for each analysis/field):
        {'ALC': {'ALC': '13.55',
                 'DefaultResult': 'ALC',
                 'Remarks': ''},
         'CO2': {'CO2': '0.66',
                 'DefaultResult': 'CO2',
                 'Remarks': ''},
         'Date': {'Date': '21/11/2013',
                  'DefaultResult': 'Date',
                  'Remarks': ''},
         'Malo': {'DefaultResult': 'Malo',
                  'Malo': '0.26',
                  'Remarks': ''},
         'Meth': {'DefaultResult': 'Meth',
                  'Meth': '0.58',
         'Rep #': {'DefaultResult': 'Rep #',
                  'Remarks': '',
                  'Rep #': '1'}
        }
    """
    if 'Date' in values and 'Time' in values:
        try:
            dtstr = '%s %s' % (values.get('Date')['Date'], values.get('Time')['Time'])
            # 2/11/2005 13:33 PM
            from datetime import datetime
            dtobj = datetime.strptime(dtstr, '%d/%m/%Y %H:%M %p')
            dateTime = dtobj.strftime("%Y%m%d %H:%M")
        except Exception:
            pass
        del values['Date']
        del values['Time']
    # Adding the date, time and calibration inside each analysis service result.
    # I'm adding the calibration number here because it is the way we can avoid
    # WINE-76 easly
    for keyword in values.keys():
        values[keyword]['DateTime'] = dateTime
        values[keyword]['Calibration'] = self._calibration
    # First, we must find if already exists a row with results for
    # the same date, in order to take into account replicas, Mean
    # and Standard Deviation
    rows = self.getRawResults().get(resid, [])
    row, rows = self._extractrowbycalibration(rows, self._calibration)
    is_std = values.get('Rep #',{}).get('Rep #','') == 'Sd'
    is_mean = values.get('Rep #',{}).get('Rep #','') == 'Mean'
    if is_std:
        # Add the results of Standard Deviation. For each acode, add
        # the Standard Result
        del values['Rep #']
        for key, value in six.iteritems(values):
            row['Sd-%s' % key] = value
    elif is_mean:
        # Remove the # item and override with new values
        row = values
        del row['Rep #']
    else:
        # Override with new values
        row = values
    rows.append(row)
    isfirst = True
    for row in rows:
        WinescanCSVParser.METHOD_NAME(self, resid, row, isfirst)
        isfirst = False