SID#6 Detecting Structural Changes and Outliers in Longitudinal Data

Automatically detect and display structural changes in longitudinal data using SAS procedures and a SAS Datastep This session explains how you can automatically detect structural changes like breakpoints and outliers in your longitudinal data. You can use SAS/STAT procedures like the ADAPTIVEREG procedure or ETS procedures like the X13 procedure for that. For an automated solution you then want to insert and label reference lines into your line-chart that indicate these events in your data. The focus is on the automation of this task. You can always add reference lines using the REFLINE statement in the SGPLOT procedure. The method that is described here, uses output values from SAS analytics procedures to automatically position and label the reference lines, instead of having to rewrite the REFLINE code every time your re-run the analysis. https://sasensei.com/flash/run/250