What if all the phenomena we study in the social sciences followed the concepts of emergence?

Many components interact to form higher order behavior and it is this behavior we observe when we study neurons, heart rate, attitudes, people, and groups. These higher order behaviors are complexly related to the lower order parts and thus there is a direct conflict between how we choose to study phenomena in the social sciences and how they function.

For example, our current methods seek causality while causality is instead incredibly complex and illusive and our current statistic are often based on a single moment in time or when time is included the description is often just that of a trajectory.

This book embraces a dynamical systems approach addressing how our methods and statistics would need to change under a world of emergence. It lays out a statistical approach using the study of phenomena through time, by looking for patterns and assessing the stability of those patterns. It capitalizes on centuries of mathematical theory integrated with regression, multilevel modeling, and structural equation modeling in an attempt to produce an integrated solution for quantitative reasoning in the social sciences.