In our standard graphics, we usually present summary statistics only. The exception is the Kaplan-Meier plot showing also individual patients. Showing individual patients effectively tells us so much more about e.g. clusters, outliers, and extreme values. Join Benjamin and I while we dive deep into the following points:
- Show uncertainty
- Show actual number of patients
- Give a feeling for the evidence
- Connect to the physicians seeing the individual patients
- Increase transparency
How to create:
- Spaghetti plot
- Slope graph
- Using jittering for categorical data or thickness based on numbers of patients
- Scatterplots
- Animations over time
- Heat maps
- Bar charts with symbols for the patients
- Kaplan-Meier
- Cumulative distribution function
- Waterfall plots
- Flowing data example of categorical data over time (find it here: https://flowingdata.com/2015/12/15/a-day-in-the-life-of-americans/)
Additional features:
- Highlight the group means
- Making it interactive with hover over or filters or selections
- Sorting is crucial
- Combination with charts displaying group differences
Solve problems:
- Unbalanced treatment groups
- Avoid over cluttered graphs
- Time to read and explain complex graphs
- Time needed to create complex graphs
- Problems obscuring small but meaningful differences
Listen to this interesting episode and share this with your friends and colleagues!
