Randy Neil Biostats 24: USMLE Step 1, 2CK, 3 - Biostatistics: Cohen's Kappa, Kendall's Tau, Pearson Correlation Coefficient

Episode Notes

USMLE purpose: Distinguish Cohen’s kappa, Kendall’s tau, and Pearson correlation coefficient when interpreting agreement and correlation questions.

How to use this page

Decide whether the question is about agreement, ordinal association, or linear correlation.
Match the statistic to the data type.
Remember that correlation does not imply causation.
Use the rapid recall toggles before the practice questions.

Episode metadata

Field	Details
Episode	Randy Neil Biostats 24
Topic	Cohen's kappa, Kendall's tau, Pearson correlation
Runtime	10 min
Published	2023-03-07
Source	Open YouTube video

One-liner

Use Cohen’s kappa for agreement between raters, Kendall’s tau for ordinal/ranked association, and Pearson r for linear correlation between continuous variables.

Statistic selection table

Statistic	Best use	Board-style clue
Cohen’s kappa	Inter-rater agreement beyond chance	Two clinicians/radiologists agree on diagnosis
Kendall’s tau	Ordinal/ranked association	Rank order, nonparametric ordinal data
Pearson correlation coefficient	Linear correlation between continuous variables	Scatterplot, r value, straight-line relationship

Pearson r interpretation

r value	Meaning
+1	Perfect positive linear correlation
0	No linear correlation
-1	Perfect negative linear correlation

Anki-style rapid recall

Which statistic measures inter-rater agreement?

Cohen’s kappa.

Which statistic is used for ranked/ordinal association?

Kendall’s tau.

Which statistic measures linear correlation?

Pearson correlation coefficient.

Practice Question

Two radiologists independently classify chest x-rays as pneumonia present or absent. Which statistic is most appropriate to measure agreement?

A) Pearson r
B) Cohen’s kappa
C) Relative risk
D) NNT

Reveal answer & explanation

Answer: B) Cohen’s kappa

Cohen’s kappa measures inter-rater agreement beyond chance.