Step 5: Visualise temporal symmetry

Introduction

In this vignette we will explore the functionality and arguments of a set of functions that will help us to understand and visualise the temporal symmetry results (produced Step 4: Obtain aggregated data on temporal symmetry). In particular, we will delve into the following function:

  • plotTemporalSymmetry(): to plot the temporal symmetry.

This function builds-up on previous functions, such as generateSequenceCohortSet() and summariseTemporalSymmetry() function.

Let’s regather the output from summariseTemporalSymmetry()

temporal_symmetry <- summariseTemporalSymmetry(cohort = cdm$intersect)

With this established, much like summariseSequenceRatios(), the object temporal_symmetry could then be fed into tableTemporalSymmetry() or plotTemporalSymmetry() to visualise the results:

tableTemporalSymmetry(result = temporal_symmetry)
Marker name Estimate name
Variable level
-390 -360 -330 -300 -270 -240 -180 -150 -120 -90 -60 30 60 90 120 150 180 210 240 270 300 330 360
GiBleed; aspirin
amoxicillin 30_days_ly_count 1 2 1 1 2 2 3 7 2 5 4 4 1 3 2 1 3 3 5 6 4 6 4
 
plotTemporalSymmetry(result = temporal_symmetry)

Note that the \(x\) axis is the time, which we recall to be the initiation of the marker minus the initiation of the index. The unit of the time difference here is 30 days as this is the default from summarisTemporalSymmetry().

This is the end of the vignette, please cite our paper and let us know of any bugs or improvements we can make - have fun with the package!