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

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