Patricia sends a plot contrasting survival curves for a control and a treatment group. Her initial graphic was made with Graphpad.
There is not much to say about the visualisation type. Survival curves are designed to display the trends in survival probabilities over time for one or more groups of individuals.
However, there are a few things that can be improved in the plot:
Reduce some unnecessary blank space in the plot by adjusting the scale and removing the legend
Unlike other plot types, 0 is not necessarily a reference level (100 is).
Use transparency to avoid hiding overlapping lines and censoring points
Overlapping is made explicit by a darker shade. Notice how one of the censoring points at the tip of the curve was hidden in the initial plot.
Display unit of time in the axis label
Always display the units of measure explicitly in the axes, unless it’s obvious or unambiguous. And even then, it’s often better to be explicit.
Integrate the legend into the plot
Besides saving some plot space, this helps by removing the need to go back and forth from the legend to the plot in order to check which group is which.
Use meaningful colours to represent control and test groups.
Red and blue are “symmetric”, they don’t convey any meaning and could have been reversed. Instead, grey feels like something that is not highlighted, a background situation, or a baseline measure. Thus, appropriate for the control group. Whereas a bright, contrasting colour such as orange is useful for a target group of interest. The focus of the study. The treatment group.
This gives the following basic reformulation of the initial figure that could work well on a journal article.
