The Banksia plot: a method for visually comparing point estimates and confidence intervals across datasets

Abstract

Objectives

In research evaluating statistical analysis methods, a common aim is to compare point estimates and CIs calculated from different analyses. This can be challenging when the outcomes (and their scale ranges) differ across datasets. We therefore developed a graphical method, the “Banksia plot”, to facilitate pairwise comparisons of different statistical analysis methods by plotting and comparing point estimates and CIs from each analysis method, both within and across datasets.

Study Design and Setting

The plot is constructed in three stages. Stage 1: To compare the results of two statistical analysis methods, for each dataset, the point estimate from the reference analysis method is centered on zero, and its confidence limits are scaled to range from −0.5 to 0.5. The same centering and scale adjustment values are then applied to the corresponding comparator analysis point estimate and confidence limits. Stage 2: A Banksia plot is constructed by plotting the centered and scaled point estimates from the comparator method for each dataset on a rectangle centered at zero, ranging from −0.5 to 0.5, which represents the reference method results. Stage 3: Optionally, a matrix of Banksia plots is graphed, showing all pairwise comparisons from multiple analysis methods. We illustrate the Banksia plot using two examples.

Results

Illustration of the Banksia plot demonstrates how the plot makes it immediately apparent whether there are differences in point estimates and CIs when using different analysis methods (example 1) or different data extractors (example 2). Furthermore, we demonstrate how different bases for ordering the CIs can be used to highlight particular differences (ie, in point estimates or CI widths).

Conclusion

The Banksia plot provides a visual summary of pairwise comparisons of different analysis methods, allowing patterns and trends in the point estimates and CIs to be easily identified.