Using linear models to model change in healthcare

What is it about?

This paper introduces a technique to model change in retrospective studies using linear segments. This can aid in identifying hidden trends in data.

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Why is it important?

Retrospective data is increasingly abundant, but researchers often rely on prospective trials to distinguish association from causation. Using segmented linear regression in retrospective studies can yield more information from that large amount of retrospective data available, and provide more information to guide prospective trials.