Measuring Agreement Categorical vs Continuous Variables (Lin's CCC, Bland Altman plots, MAE) скачать в хорошем качестве

Measuring Agreement Categorical vs Continuous Variables (Lin's CCC, Bland Altman plots, MAE)

In this concise tutorial, master how to measure agreement between both categorical and continuous data. First, learn the kappa statistic—calculating raw agreement vs. chance agreement using 2×2 tables, and interpreting κ values from poor to almost perfect. Then delve into continuous metrics: Pearson’s correlation for association, Lin’s Concordance Correlation Coefficient for bias-adjusted agreement, mean absolute error (MAE) with MAE plots, and Bland–Altman plots to visualize bias and limits of agreement. With step-by-step animations, on-screen formulas, and real-world examples like rater concordance and instrument validation, you’ll know which metric best fits your study’s needs.