Updating the Theory of Compliance with Big Data Analysis via the Key Indicator Methodology

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.

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About Dr Fiene

Dr. Rick Fiene has spent his professional career in improving the quality of child care in various states, nationally, and internationally. He has done extensive research and publishing on the key components in improving child care quality through an early childhood program quality indicator model of training, technical assistance, quality rating & improvement systems, professional development, mentoring, licensing, risk assessment, differential program monitoring, and accreditation. Dr. Fiene is a retired professor of human development & psychology (Penn State University) where he was department head and director of the Capital Area Early Childhood Research and Training Institute.
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