content: """RAND Health Insurance Experiment Data"""
  
  __docformat__ = 'restructuredtext'
  
  COPYRIGHT   = """This is in the public domain."""
  TITLE       = __doc__
  SOURCE      = """
  The data was collected by the RAND corporation as part of the Health
  Insurance Experiment (HIE).
  
  http://www.rand.org/health/projects/hie.html
  
  This data was used in::
  
      Cameron, A.C. amd Trivedi, P.K. 2005.  `Microeconometrics: Methods
          and Applications,` Cambridge: New York.
  
  And was obtained from: <http://cameron.econ.ucdavis.edu/mmabook/mmadata.html>
  
  See randhie/src for the original data and description.  The data included
  here contains only a subset of the original data.  The data varies slightly
  compared to that reported in Cameron and Trivedi.
  """
  
  DESCRSHORT  = """The RAND Co. Health Insurance Experiment Data"""
  
  DESCRLONG   = """"""
  
  NOTE        = """::
  
      Number of observations - 20,190
      Number of variables - 10
      Variable name definitions::
  
          mdvis   - Number of outpatient visits to an MD
          lncoins - ln(coinsurance + 1), 0 <= coninsurance <= 100
          idp     - 1 if individual deductible plan, 0 otherwise
          lpi     - ln(max(1, annual participation incentive payment))
          fmde    - 0 if idp = 1; ln(max(1, MDE/(0.01 coinsurance))) otherwise
          physlm  - 1 if the person has a physical limitation
          disea   - number of chronic diseases
          hlthg   - 1 if self-rated health is good
          hlthf   - 1 if self-rated health is fair
          hlthp   - 1 if self-rated health is poor
          (Omitted category is excellent self-rated health)
  """
  
  from numpy import recfromtxt, column_stack, array
  from statsmodels.datasets import utils as du
  from os.path import dirname, abspath
  
  PATH = '%s/%s' % (dirname(abspath(__file__)), 'randhie.csv')
  
  def load():
      """
      Loads the RAND HIE data and returns a Dataset class.
  
      ----------
      endog - response variable, mdvis
      exog - design
  
      Returns
      Load instance:
          a class of the data with array attrbutes 'endog' and 'exog'
      """
      data = _get_data()
      return du.process_recarray(data, endog_idx=0, dtype=float)
  
  def load_pandas():
      """
      Loads the RAND HIE data and returns a Dataset class.
  
      ----------
      endog - response variable, mdvis
      exog - design
  
      Returns
      Load instance:
          a class of the data with array attrbutes 'endog' and 'exog'
      """
      from pandas import read_csv
      data = read_csv(PATH)
      return du.process_recarray_pandas(data, endog_idx=0)
  
  def _get_data():
      with open(PATH, "rb") as f:
          data = recfromtxt(f, delimiter=",", names=True, dtype=float)
          return data
  