Bland-Altman Plot Fundamentals
📌 A Bland-Altman plot is a graphical method used to compare two measurements by plotting the differences between them against their averages.
📊 This technique helps visualize the degree of agreement between two raters and identify any systematic bias.
🧪 An example involves comparing two blood glucose meters (GlucoClassic and GlucoNew) using paired measurements from 10 patients.

Plot Construction Steps
🔢 For each pair of measurements, calculate the difference (e.g., $105 - 100 = 5$) and the mean (e.g., $(105 + 100) / 2 = 102.5$).
📈 Plot the difference on the Y-axis and the mean value on the X-axis for all pairs.
⚖️ Calculate the mean of the differences (which represents the bias, e.g., 3.7 in the example) and the standard deviation of the differences (e.g., 1.25).

Interpreting Results and Agreement Limits
📉 The bias (mean difference) indicates the average difference; a value near zero suggests high agreement, while drifting away signals systematic bias.
📏 The 95% limits of agreement are calculated as: $\text{Mean} \pm 1.96 \times \text{Standard Deviation}$. In the example, this range was $3.7 \pm 1.96 \times 1.25$, resulting in limits of $6.25$ and $1.25$.
🔎 Scatter analysis looks for patterns; random scatter is positive, while funneling suggests proportional biases where agreement varies across the measurement magnitude range.

Key Points & Insights
➡️ The Bland-Altman plot is essential for assessing inter-rater reliability beyond simple correlation coefficients.
➡️ A mean difference significantly different from zero immediately flags a systematic bias between the two measurement methods.
➡️ The limits of agreement provide the critical 95% confidence interval for the observed differences, defining the acceptable variability range.
🛠️ Online tools like dataviz.com offer free services to generate Bland-Altman plots by inputting paired metric data.

📸 Video summarized with SummaryTube.com on Dec 19, 2025, 16:08 UTC