SOCIAL SCIENCE MACHINE FOR MEASURING LATENT VARIABLE MODELS WITH BIG DATA SURVEYS

摘要

The current invention is a Social Science Machine designed to articulate social science theory-based latent variable models; to operationalize such models through survey research methodologies; and to obtain valid comparative measurements of such latent variable models from such methodologies. The embodiment described herein is the performance measurement of Well-Being Programs which are programs designed to improve the physical, or psychological health; social connectivity; coping capabilities; and development of their participants. Measurement of Well-Being Programs is fraught with threats to validity from Selection and Response Biases. The invention explicitly deals with Selection and Response Biases and can be used to establish a virtuous cycle of feedback to drive performance improvements in human services analogous to what has been achieved in manufacturing with Statistical Process Control. The invention employs a collaborative, multi-entity approach for the standardized collection and analysis of Big Survey Data derived from multiple organizations.