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

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Bibliográfalaš dieđut
Publikašuvnnas:Journal of Clinical Epidemiology vol. 177 (Jan 2025)
Váldodahkki: Turner, Simon L
Eará dahkkit: Karahalios, Amalia, Korevaar, Elizabeth, McKenzie, Joanne E
Almmustuhtton:
Elsevier Limited
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100 1 |a Turner, Simon L  |u School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Victoria, Australia 
245 1 |a The Banksia plot: a method for visually comparing point estimates and confidence intervals across datasets 
260 |b Elsevier Limited  |c Jan 2025 
513 |a Journal Article 
520 3 |a 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. 
653 |a Statistics 
653 |a Plotting 
653 |a Graphical methods 
653 |a Datasets 
653 |a Fatalities 
653 |a Statistical analysis 
653 |a Confidence limits 
653 |a Confidence intervals 
653 |a Estimates 
653 |a Antibiotics 
653 |a Comparators 
653 |a Statistical methods 
653 |a Medical statistics 
700 1 |a Karahalios, Amalia  |u Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne 3010, Victoria, Australia 
700 1 |a Korevaar, Elizabeth  |u School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Victoria, Australia 
700 1 |a McKenzie, Joanne E  |u School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Victoria, Australia 
773 0 |t Journal of Clinical Epidemiology  |g vol. 177 (Jan 2025) 
786 0 |d ProQuest  |t Healthcare Administration Database 
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