# Agreement plot

An agreement plot shows the agreement between two binary or semi-quantitative methods.

*Bangdiwala (2013)* devised the agreement plot as a complement to the kappa or
B-statistics. It is invaluable for assessing agreement as it gives a visual impression that no
summary statistic can convey.

The agreement plot is a visual representation of a k by k square contingency table. Each black rectangle represents the marginal totals of the rows and columns. Shaded boxes represent the agreement based on the diagonal cell frequencies; they are positioned inside the rectangles using the sum of the off-diagonal cell frequencies from the same row and column. The partial agreement in the off-diagonal cells can be represented similarly with decreased shading based on the distance from the diagonal. The visualization is affected by the order of the categories, and so the plot is only useful for ordinal or binary data. The plot can have the origin at the bottom-left corner, or at the top-left where it more clearly mimics the contingency table.

Perfect agreement is represented by rectangles that are all perfect squares, with corners on the diagonal identity line, and with shaded boxes equal to the rectangle. Lesser agreement is represented by the area of shaded boxes compared to the area of rectangles. The path of the rectangles, how they deviate from the 45-degree identity line, represents bias in the marginal totals.

**Related concepts**

- What is Analyse-it?
- What's new?
- Administrator's Guide
- User's Guide
- Statistical Reference Guide
- Distribution
- Compare groups
- Compare pairs
- Contingency tables
- Correlation and association
- Principal component analysis (PCA)
- Factor analysis (FA)
- Item reliability
- Fit model
- Method comparison
- Correlation coefficient
- Scatter plot
- Fit Y on X
- Fitting ordinary linear regression
- Fitting Deming regression
- Fitting Passing-Bablok regression
- Linearity
- Residual plot
- Checking the assumptions of the fit
- Average bias
- Estimating the bias between methods at a decision level
- Testing commutability of other materials
- Difference plot (Bland-Altman plot)
- Fit differences
- Plotting a difference plot and estimating the average bias
- Limits of agreement (LoA)
- Plotting the Bland-Altman limits of agreement
- Mountain plot (folded CDF plot)
- Plotting a mountain plot
- Partitioning and reducing the measuring interval
- Agreement measures for binary and semi-quantitative data
- Chance corrected agreement measures for binary and semi-quantitative data
- Agreement plot
- Estimating agreement between two binary or semi-quantitative methods
- Study design
- Study design for qualitative methods
- Measurement systems analysis (MSA)
- Reference interval
- Diagnostic performance
- Control charts
- Process capability
- Pareto analysis
- Study Designs
- Bibliography

Version 5.65

Published 14-Aug-2020