There is a major movement within the human services involving big data where rather than selecting samples to do analyses state/provincial agencies have the capability to provide basically population data.  For the Theory of Regulatory Compliance as it involves the Licensing Key Indicator Methodology, selection criteria and the dichotomization of data are changing dramatically because of the increased cell sizes in determining and generating the Licensing Key Indicators.

For example, in the past, the Licensing Key Indicator Methodology always utilized a 25/50/25 dichotomization model for segregating high compliance from low compliance facilities.  However, with big data being available, cell sizes are much more robust in which this dichotomization model can be increased to 12.5/75/12.5.   The move to this model helps to decrease the number of false negatives while at the same time increasing phi coefficients.  By doing this, the Licensing Key Indicators generated are very robust and highly predictive.

The following Licensing Key Indicators continue to be identified in state/provincial analyses and results (all these Indicators are from the original ASPE Research Brief: 13 Indicators of Quality Child Care):

• Proper Supervision,
• Children are properly immunized,
• The facility is hazard free,
• Reporting of child abuse, and
• Staff are trained in CPR and first aid.