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

Companion data for the creation of a banksia plot:Background:In research evaluating statistical analysis methods, a common aim is to compare point estimates and confidence intervals (CIs) calculated from different analyses. This can be challenging when the outcomes (and their scale ranges) differ across datasets. We therefore developed a plot to facilitate pairwise comparisons of point estimates and confidence intervals from different statistical analyses both within and across datasets.Methods:The plot was developed and refined over the course of an empirical study. To compare results from a variety of different studies, a system of centring and scaling is used. Firstly, the point estimates from reference analyses are centred to zero, followed by scaling confidence intervals to span a range of one. The point estimates and confidence intervals from matching comparator analyses are then adjusted by the same amounts. This enables the relative positions of the point estimates and CI widths to be quickly assessed while maintaining the relative magnitudes of the difference in point estimates and confidence interval widths between the two analyses. Banksia plots can be graphed in a matrix, showing all pairwise comparisons of multiple analyses. In this paper, we show how to create a banksia plot and present two examples: the first relates to an empirical evaluation assessing the difference between various statistical methods across 190 interrupted time series (ITS) data sets with widely varying characteristics, while the second example assesses data extraction accuracy comparing results obtained from analysing original study data (43 ITS studies) with those obtained by four researchers from datasets digitally extracted from graphs from the accompanying manuscripts.Results:In the banksia plot of statistical method comparison, it was clear that there was no difference, on average, in point estimates and it was straightforward to ascertain which methods resulted in smaller, similar or larger confidence intervals than others. In the banksia plot comparing analyses from digitally extracted data to those from the original data it was clear that both the point estimates and confidence intervals were all very similar among data extractors and original data.Conclusions:The banksia plot, a graphical representation of centred and scaled confidence intervals, provides a concise summary of comparisons between multiple point estimates and associated CIs in a single graph. Through this visualisation, patterns and trends in the point estimates and confidence intervals can be easily identified.This collection of files allows the user to create the images used in the companion paper and amend this code to create their own banksia plots using either Stata version 17 or R version 4.3.1

用于绘制班克西亚图（banksia plot）的配套数据集：
背景：在评估统计分析方法的研究中，常见目标是比较不同分析方法计算得到的点估计（point estimate）与置信区间（confidence interval, CI）。当不同数据集的结局指标（及其量纲范围）存在差异时，此类比较颇具挑战性。为此，我们开发了一款绘图工具，以支持在单数据集内及跨数据集场景下，对不同统计分析的点估计与置信区间进行两两比较。
方法：本绘图工具依托一项实证研究的过程开发并优化。为对比多项不同研究的结果，我们采用了中心化与标准化的处理体系：首先将参考分析的点估计值中心化至0，随后将置信区间缩放至跨度为1的区间；随后将匹配的对照分析的点估计与置信区间按相同比例进行调整。此举可在保留两次分析间点估计差值与置信区间宽度相对幅度的同时，便于快速评估点估计的相对位置与置信区间宽度。班克西亚图可通过矩阵形式绘制，展示多组分析的全部两两比较结果。本文将介绍班克西亚图的绘制方法，并展示两个应用案例：第一个案例为一项实证评估，旨在对比190个特征差异显著的间断时间序列（interrupted time series, ITS）数据集上不同统计方法的分析结果差异；第二个案例则评估数据提取准确率，对比分析原始研究数据（43项间断时间序列研究）的结果，与4名研究人员从随附手稿的图表中数字化提取的数据集所得到的分析结果。
结果：在统计方法对比的班克西亚图中，可清晰观察到点估计的平均差异为0，且可直观确定哪些方法得到的置信区间更小、相近或更大。在对比数字化提取数据与原始数据的分析结果的班克西亚图中，可明确所有数据提取人员与原始数据的点估计及置信区间均高度相似。
结论：班克西亚图是一种对中心化且标准化后的置信区间进行可视化的图形形式，可在单张图表中简洁总结多组点估计及其对应置信区间的对比结果。通过该可视化工具，可轻松识别点估计与置信区间的模式与趋势。
本文件集合可供用户生成本配套论文中使用的图像，且允许用户修改代码，使用Stata 17或R 4.3.1版本自行绘制班克西亚图。